# Hermes Agent - Development Guide

Instructions for AI coding assistants and developers working on the hermes-agent codebase.

**Never give up on the right solution.**

## What Hermes Is

Hermes is a personal AI agent that runs the same agent core across a CLI, a
messaging gateway (Telegram, Discord, Slack, and ~20 other platforms), a TUI,
and an Electron desktop app. It learns across sessions (memory + skills),
delegates to subagents, runs scheduled jobs, and drives a real terminal and
browser. It is extended primarily through **plugins and skills**, not by
growing the core.

Two properties shape almost every design decision and are the lens for
reviewing any change:

- **Per-conversation prompt caching is sacred.** A long-lived conversation
  reuses a cached prefix every turn. Anything that mutates past context,
  swaps toolsets, or rebuilds the system prompt mid-conversation invalidates
  that cache and multiplies the user's cost. We do not do it (the one
  exception is context compression).
- **The core is a narrow waist; capability lives at the edges.** Every model
  tool we add is sent on every API call, so the bar for a new *core* tool is
  high. Most new capability should arrive as a CLI command + skill, a
  service-gated tool, or a plugin — not as core surface.

## Contribution Rubric — What We Want / What We Don't

This is the project's intent layer. Use it two ways:

1. **For humans and for your own work** — what gets merged and what gets
   rejected, so a contribution aims at the target.
2. **For automated review (the triage sweeper)** — guidance on when a PR is
   safe to close on the three allowed reasons (`implemented_on_main`,
   `cannot_reproduce`, `incoherent`) and, just as important, **when NOT to
   close** one. Taste-based "we don't want this / out of scope" closes are NOT
   an automated decision — those stay with a human maintainer. The sweeper's
   job here is to recognize design intent and *avoid wrongly closing a
   legitimate contribution*, not to make the won't-implement call itself.

Read the balance right: Hermes ships a **lot** — most merges are bug fixes to
real reported behavior, and the product surface (platforms, channels,
providers, models, desktop/TUI features) expands aggressively and on purpose.
The restraint below is aimed squarely at the **core agent + the model tool
schema**, the one place where every addition is paid for on every API call.
"Smallest footprint" governs *how a capability is wired into the core*, NOT
whether the product is allowed to grow. We are expansive at the edges and
conservative at the waist.

### What we want

- **Fix real bugs, well.** The bulk of what lands is `fix(...)` against an
  actual reported symptom. A good fix reproduces the symptom on current
  `main`, points to the exact line where it manifests, and fixes the whole bug
  class — sibling call paths included — not just the one site the reporter hit.
- **Expand reach at the edges.** New platform adapters, channels, providers,
  models, and desktop/TUI/dashboard features are welcome and land routinely,
  including large ones (a new messaging channel, a session-cap feature, a
  Windows PTY bridge). Breadth in the product is a goal, not a footprint
  concern — as long as it integrates with the existing setup/config UX
  (`hermes tools`, `hermes setup`, auto-install) rather than bolting on a raw
  env var.
- **Refactor god-files into clean modules.** Extracting a multi-thousand-line
  cluster out of `cli.py` / `run_agent.py` / `gateway/run.py` into a focused
  mixin or module is wanted work, even when the diff is huge and mechanical
  (large `+N/-N` refactors merge regularly). The "every line traces to the
  request" test applies to *feature* PRs; a declared refactor's request IS the
  extraction.
- **Keep the core narrow.** New *model tools* are the expensive exception —
  every tool ships on every API call. Prefer, in order: extend existing code →
  CLI command + skill → service-gated tool (`check_fn`) → plugin → MCP server
  in the catalog → new core tool (last resort). See "The Footprint Ladder."
- **Extend, don't duplicate.** Before adding a module/manager/hook, check
  whether existing infrastructure already covers the use case. When several PRs
  integrate the same *category*, design one shared interface instead of merging
  them one at a time (see the ABC + orchestrator note under the Footprint
  Ladder).
- **Behavior contracts over snapshots.** Tests should assert how two pieces of
  data must relate (invariants), not freeze a current value (model lists,
  config version literals, enumeration counts). See "Don't write
  change-detector tests."
- **E2E validation, not just green unit mocks.** For anything touching
  resolution chains, config propagation, security boundaries, remote
  backends, or file/network I/O, exercise the real path with real imports
  against a temp `HERMES_HOME`. Mocks hide integration bugs.
- **Cache-, alternation-, and invariant-safe.** Preserve prompt caching, strict
  message role alternation (never two same-role messages in a row; never a
  synthetic user message injected mid-loop), and a system prompt that is
  byte-stable for the life of a conversation.
- **Contributor credit preserved.** Salvage external work by cherry-picking
  (rebase-merge) so authorship survives in git history; don't reimplement from
  scratch when you can build on top.

### What we don't want (rejected even when well-built)

- **Speculative infrastructure.** Hooks, callbacks, or extension points with no
  concrete consumer. Adding a hook is easy; removing one after plugins depend
  on it is hard. A hook is NOT speculative if a contributor has a real, stated
  use case — even if the consumer ships separately.
- **New `HERMES_*` env vars for non-secret config.** `.env` is for secrets
  only (API keys, tokens, passwords). All behavioral settings — timeouts,
  thresholds, feature flags, display prefs — go in `config.yaml`. Bridge to an
  internal env var if the mechanism needs one, but user-facing docs point to
  `config.yaml`. Reject PRs that tell users to "set X in your .env" unless X
  is a credential.
- **A new core tool when terminal + file already do the job, or when a skill
  would.** If the only barrier is file visibility on a remote backend, fix the
  mount, not the toolset.
- **Lazy-reading escape hatches on instructional tools.** No `offset`/`limit`
  pagination on tools that load content the agent must read fully (skills,
  prompts, playbooks). Models will read page 1 and skip the rest.
- **"Fixes" that destroy the feature they secure.** A mitigation that kills the
  feature's purpose is the wrong mitigation. Read the original commit's intent
  (`git log -p -S`) before restricting behavior; find a fix that preserves the
  feature.
- **Outbound telemetry / usage attribution without opt-in gating.** No new
  analytics, third-party identifier tagging, or attribution tags until a
  generic user-facing opt-in (config gate + setup prompt + `hermes tools`
  toggle) exists. Park behind a label, do not merge.
- **Change-detector tests, cache-breaking mid-conversation, dead code wired in
  without E2E proof, and plugins that touch core files.** Plugins live in their
  own directory and work within the ABCs/hooks we provide; if a plugin needs
  more, widen the generic plugin surface, don't special-case it in core.

### Before you call it a bug — verify the premise (and when NOT to close)

The most common reason a well-written PR gets closed is not code quality — it
is that the change is built on a **wrong premise**, or it treats an
**intentional design as a gap**. These patterns cut both ways: they tell a
human reviewer what to scrutinize, and they tell the automated sweeper when a
PR is NOT safe to close as `implemented_on_main` / `cannot_reproduce` (when in
doubt, leave it open for a human). They are distilled from real closes.

- **"Intentional design, not a gap."** A limitation that looks like an
  oversight is often deliberate. Before "fixing" a missing link or a
  restriction, ask whether the isolation IS the design. Example: profiles are
  independent islands on purpose — a PR adding live config inheritance from the
  default profile was closed because coupling profiles together is exactly what
  the design prevents (the copy-at-creation `--clone` path already covers the
  legitimate "start from my default" case). Read the original commit's intent
  (`git log -p -S "<symbol>"`) before assuming something is unfinished.
- **"The premise doesn't hold against how X actually works."** A PR's
  justification frequently rests on a wrong mental model of an existing
  mechanism. Trace the real code/runtime before accepting the rationale. Two
  real closes: a rate-limit "re-probe during cooldown" PR (the breaker only
  trips on a *confirmed-empty* account bucket, so re-probing just hammers a
  bucket we've already proven empty); a usage-accumulation fix whose new branch
  **never executes at runtime** because an earlier guard already popped the
  state it depended on. If you can't point to the exact line where the bug
  manifests AND show the fix changes that line's behavior, you haven't verified
  the premise.
- **"This fix was wrong — the absence/omission was deliberate."** Adding the
  obvious-looking missing piece can break things the omission was protecting.
  Example: restoring "missing" `__init__.py` files made a test tree importable
  as a dotted package that shadowed the real plugin, deleting its `register()`
  at import time. The absence was load-bearing.
- **"Overreached / resurrected an approach we'd moved past."** Scope creep that
  supersedes an agreed-on base, or revives a direction the maintainers
  deliberately closed, gets rejected even when the code works. Keep the change
  to the narrow piece that was actually agreed; offer the rest as a focused
  follow-up.

The throughline: **verify the claim AND the intent against the codebase before
writing or merging a fix.** A confirmed reproduction on current `main` plus a
line-level account of where the fix acts beats a plausible-sounding rationale
every time. When in doubt about intent, it is cheaper to ask than to ship a
fix that fights the design.

### The Footprint Ladder (new capability decision)

Each rung adds more permanent surface than the one above. Choose the highest
(least-footprint) rung that correctly solves the problem:

1. **Extend existing code** — the capability is a variation of something that
   already exists. Zero new surface.
2. **CLI command + skill** — manages config/state/infra expressible as shell
   commands. The agent runs `hermes <subcommand>` guided by a skill. Zero
   model-tool footprint. Default choice for subscriptions, scheduled tasks,
   service setup. Examples: `hermes webhook`, `hermes cron`, `hermes tools`.
3. **Service-gated tool (`check_fn`)** — needs structured params/returns AND
   only appears when a prerequisite is configured. Zero footprint otherwise.
   Examples: Home Assistant tools (gated on token), memory-provider tools.
4. **Plugin** — third-party/niche/user-specific capability that doesn't ship in
   core. Lives in `~/.hermes/plugins/` or a pip package, discovered at runtime.
5. **MCP server (in the catalog)** — if the capability genuinely needs to be a
   tool (structured I/O the agent invokes) but isn't core-fundamental, prefer
   building it as an MCP server and adding it to the MCP catalog over growing
   the core toolset. The agent connects to it through the built-in MCP client;
   zero permanent core-schema footprint, and it's reusable by any MCP host.
6. **New core tool** — only when the capability is fundamental, broadly useful
   to nearly every user, and unreachable via terminal + file (or an MCP server).
   Examples of correct core tools: terminal, read_file, web_search,
   browser_navigate.

When 3+ open PRs try to integrate the same *category* of thing (memory
backends, providers, notifiers), don't merge them one at a time — design an
ABC + orchestrator, wrap the existing built-in as the first provider, and turn
the competing PRs into plugins against that interface.

## Development Environment

```bash
# Prefer .venv; fall back to venv if that's what your checkout has.
source .venv/bin/activate   # or: source venv/bin/activate
```

`scripts/run_tests.sh` probes `.venv` first, then `venv`, then
`$HOME/.hermes/hermes-agent/venv` (for worktrees that share a venv with the
main checkout).

## Project Structure

File counts shift constantly — don't treat the tree below as exhaustive.
The canonical source is the filesystem. The notes call out the load-bearing
entry points you'll actually edit.

```
hermes-agent/
├── run_agent.py          # AIAgent class — core conversation loop (~12k LOC)
├── model_tools.py        # Tool orchestration, discover_builtin_tools(), handle_function_call()
├── toolsets.py           # Toolset definitions, _HERMES_CORE_TOOLS list
├── cli.py                # HermesCLI class — interactive CLI orchestrator (~11k LOC)
├── hermes_state.py       # SessionDB — SQLite session store (FTS5 search)
├── hermes_constants.py   # get_hermes_home(), display_hermes_home() — profile-aware paths
├── hermes_logging.py     # setup_logging() — agent.log / errors.log / gateway.log (profile-aware)
├── batch_runner.py       # Parallel batch processing
├── agent/                # Agent internals (provider adapters, memory, caching, compression, etc.)
├── hermes_cli/           # CLI subcommands, setup wizard, plugins loader, skin engine
├── tools/                # Tool implementations — auto-discovered via tools/registry.py
│   └── environments/     # Terminal backends (local, docker, ssh, modal, daytona, singularity)
├── gateway/              # Messaging gateway — run.py + session.py + platforms/
│   ├── platforms/        # Adapter per platform (telegram, discord, slack, whatsapp,
│   │                     #   homeassistant, signal, matrix, mattermost, email, sms,
│   │                     #   dingtalk, wecom, weixin, feishu, qqbot, bluebubbles,
│   │                     #   yuanbao, webhook, api_server, ...). See ADDING_A_PLATFORM.md.
│   └── builtin_hooks/    # Extension point for always-registered gateway hooks (none shipped)
├── plugins/              # Plugin system (see "Plugins" section below)
│   ├── memory/           # Memory-provider plugins (honcho, mem0, supermemory, ...)
│   ├── context_engine/   # Context-engine plugins
│   ├── model-providers/  # Inference backend plugins (openrouter, anthropic, gmi, ...)
│   ├── kanban/           # Multi-agent board dispatcher + worker plugin
│   ├── hermes-achievements/  # Gamified achievement tracking
│   ├── observability/    # Metrics / traces / logs plugin
│   ├── image_gen/        # Image-generation providers
│   └── <others>/         # disk-cleanup, google_meet, platforms, spotify,
│                         #   strike-freedom-cockpit, ...
├── optional-skills/      # Heavier/niche skills shipped but NOT active by default
├── skills/               # Built-in skills bundled with the repo
├── ui-tui/               # Ink (React) terminal UI — `hermes --tui`
│   └── src/              # entry.tsx, app.tsx, gatewayClient.ts + app/components/hooks/lib
├── tui_gateway/          # Python JSON-RPC backend for the TUI
├── acp_adapter/          # ACP server (VS Code / Zed / JetBrains integration)
├── cron/                 # Scheduler — jobs.py, scheduler.py
├── scripts/              # run_tests.sh, release.py, auxiliary scripts
├── website/              # Docusaurus docs site
└── tests/                # Pytest suite (~17k tests across ~900 files as of May 2026)
```

**User config:** `~/.hermes/config.yaml` (settings), `~/.hermes/.env` (API keys only).
**Logs:** `~/.hermes/logs/` — `agent.log` (INFO+), `errors.log` (WARNING+),
`gateway.log` when running the gateway. Profile-aware via `get_hermes_home()`.
Browse with `hermes logs [--follow] [--level ...] [--session ...]`.

## TypeScript Style

Applies to TypeScript across Hermes: desktop, TUI, website, and future TS packages.

- Prefer small nanostores over component state when state is shared, reused, or read by distant UI.
- Let each feature own its atoms. Chat state belongs near chat, shell state near shell, shared state in `src/store`.
- Components that render from an atom should use `useStore`. Non-rendering actions should read with `$atom.get()`.
- Do not pass state through three components when the leaf can subscribe to the atom.
- Keep persistence beside the atom that owns it.
- Keep route roots thin. They compose routes and shell; they should not become controllers.
- No monolithic hooks. A hook should own one narrow job.
- Prefer colocated action modules over hidden god hooks.
- If a callback is pure side effect, use the terse void form:
  `onState={st => void setGatewayState(st)}`.
- Async UI handlers should make intent explicit:
  `onClick={() => void save()}`.
- Prefer interfaces for public props and shared object shapes. Avoid `type X = { ... }` for object props.
- Extend React primitives for props: `React.ComponentProps<'button'>`, `React.ComponentProps<typeof Dialog>`, `Omit<...>`, `Pick<...>`.
- Table-driven beats condition ladders when mapping ids, routes, or views.
- `src/app` owns routes, pages, and page-specific components.
- `src/store` owns shared atoms.
- `src/lib` owns shared pure helpers.

## File Dependency Chain

```
tools/registry.py  (no deps — imported by all tool files)
       ↑
tools/*.py  (each calls registry.register() at import time)
       ↑
model_tools.py  (imports tools/registry + triggers tool discovery)
       ↑
run_agent.py, cli.py, batch_runner.py, environments/
```

---

## AIAgent Class (run_agent.py)

The real `AIAgent.__init__` takes ~60 parameters (credentials, routing, callbacks,
session context, budget, credential pool, etc.). The signature below is the
minimum subset you'll usually touch — read `run_agent.py` for the full list.

```python
class AIAgent:
    def __init__(self,
        base_url: str = None,
        api_key: str = None,
        provider: str = None,
        api_mode: str = None,              # "chat_completions" | "codex_responses" | ...
        model: str = "",                   # empty → resolved from config/provider later
        max_iterations: int = 90,          # tool-calling iterations (shared with subagents)
        enabled_toolsets: list = None,
        disabled_toolsets: list = None,
        quiet_mode: bool = False,
        save_trajectories: bool = False,
        platform: str = None,              # "cli", "telegram", etc.
        session_id: str = None,
        skip_context_files: bool = False,
        skip_memory: bool = False,
        credential_pool=None,
        # ... plus callbacks, thread/user/chat IDs, iteration_budget, fallback_model,
        # checkpoints config, prefill_messages, service_tier, reasoning_config, etc.
    ): ...

    def chat(self, message: str) -> str:
        """Simple interface — returns final response string."""

    def run_conversation(self, user_message: str, system_message: str = None,
                         conversation_history: list = None, task_id: str = None) -> dict:
        """Full interface — returns dict with final_response + messages."""
```

### Agent Loop

The core loop is inside `run_conversation()` — entirely synchronous, with
interrupt checks, budget tracking, and a one-turn grace call:

```python
while (api_call_count < self.max_iterations and self.iteration_budget.remaining > 0) \
        or self._budget_grace_call:
    if self._interrupt_requested: break
    response = client.chat.completions.create(model=model, messages=messages, tools=tool_schemas)
    if response.tool_calls:
        for tool_call in response.tool_calls:
            result = handle_function_call(tool_call.name, tool_call.args, task_id)
            messages.append(tool_result_message(result))
        api_call_count += 1
    else:
        return response.content
```

Messages follow OpenAI format: `{"role": "system/user/assistant/tool", ...}`.
Reasoning content is stored in `assistant_msg["reasoning"]`.

---

## CLI Architecture (cli.py)

- **Rich** for banner/panels, **prompt_toolkit** for input with autocomplete
- **KawaiiSpinner** (`agent/display.py`) — animated faces during API calls, `┊` activity feed for tool results
- `load_cli_config()` in cli.py merges hardcoded defaults + user config YAML
- **Skin engine** (`hermes_cli/skin_engine.py`) — data-driven CLI theming; initialized from `display.skin` config key at startup; skins customize banner colors, spinner faces/verbs/wings, tool prefix, response box, branding text
- `process_command()` is a method on `HermesCLI` — dispatches on canonical command name resolved via `resolve_command()` from the central registry
- Skill slash commands: `agent/skill_commands.py` scans `~/.hermes/skills/`, injects as **user message** (not system prompt) to preserve prompt caching

### Slash Command Registry (`hermes_cli/commands.py`)

All slash commands are defined in a central `COMMAND_REGISTRY` list of `CommandDef` objects. Every downstream consumer derives from this registry automatically:

- **CLI** — `process_command()` resolves aliases via `resolve_command()`, dispatches on canonical name
- **Gateway** — `GATEWAY_KNOWN_COMMANDS` frozenset for hook emission, `resolve_command()` for dispatch
- **Gateway help** — `gateway_help_lines()` generates `/help` output
- **Telegram** — `telegram_bot_commands()` generates the BotCommand menu
- **Slack** — `slack_subcommand_map()` generates `/hermes` subcommand routing
- **Autocomplete** — `COMMANDS` flat dict feeds `SlashCommandCompleter`
- **CLI help** — `COMMANDS_BY_CATEGORY` dict feeds `show_help()`

### Adding a Slash Command

1. Add a `CommandDef` entry to `COMMAND_REGISTRY` in `hermes_cli/commands.py`:
```python
CommandDef("mycommand", "Description of what it does", "Session",
           aliases=("mc",), args_hint="[arg]"),
```
2. Add handler in `HermesCLI.process_command()` in `cli.py`:
```python
elif canonical == "mycommand":
    self._handle_mycommand(cmd_original)
```
3. If the command is available in the gateway, add a handler in `gateway/run.py`:
```python
if canonical == "mycommand":
    return await self._handle_mycommand(event)
```
4. For persistent settings, use `save_config_value()` in `cli.py`

**CommandDef fields:**
- `name` — canonical name without slash (e.g. `"background"`)
- `description` — human-readable description
- `category` — one of `"Session"`, `"Configuration"`, `"Tools & Skills"`, `"Info"`, `"Exit"`
- `aliases` — tuple of alternative names (e.g. `("bg",)`)
- `args_hint` — argument placeholder shown in help (e.g. `"<prompt>"`, `"[name]"`)
- `cli_only` — only available in the interactive CLI
- `gateway_only` — only available in messaging platforms
- `gateway_config_gate` — config dotpath (e.g. `"display.tool_progress_command"`); when set on a `cli_only` command, the command becomes available in the gateway if the config value is truthy. `GATEWAY_KNOWN_COMMANDS` always includes config-gated commands so the gateway can dispatch them; help/menus only show them when the gate is open.

**Adding an alias** requires only adding it to the `aliases` tuple on the existing `CommandDef`. No other file changes needed — dispatch, help text, Telegram menu, Slack mapping, and autocomplete all update automatically.

---

## TUI Architecture (ui-tui + tui_gateway)

The TUI is a full replacement for the classic (prompt_toolkit) CLI, activated via `hermes --tui` or `HERMES_TUI=1`.

### Process Model

```
hermes --tui
  └─ Node (Ink)  ──stdio JSON-RPC──  Python (tui_gateway)
       │                                  └─ AIAgent + tools + sessions
       └─ renders transcript, composer, prompts, activity
```

TypeScript owns the screen. Python owns sessions, tools, model calls, and slash command logic.

### Transport

Newline-delimited JSON-RPC over stdio. Requests from Ink, events from Python. See `tui_gateway/server.py` for the full method/event catalog.

### Key Surfaces

| Surface | Ink component | Gateway method |
|---------|---------------|----------------|
| Chat streaming | `app.tsx` + `messageLine.tsx` | `prompt.submit` → `message.delta/complete` |
| Tool activity | `thinking.tsx` | `tool.start/progress/complete` |
| Approvals | `prompts.tsx` | `approval.respond` ← `approval.request` |
| Clarify/sudo/secret | `prompts.tsx`, `maskedPrompt.tsx` | `clarify/sudo/secret.respond` |
| Session picker | `sessionPicker.tsx` | `session.list/resume` |
| Slash commands | Local handler + fallthrough | `slash.exec` → `_SlashWorker`, `command.dispatch` |
| Completions | `useCompletion` hook | `complete.slash`, `complete.path` |
| Theming | `theme.ts` + `branding.tsx` | `gateway.ready` with skin data |

### Slash Command Flow

1. Built-in client commands (`/help`, `/quit`, `/clear`, `/resume`, `/copy`, `/paste`, etc.) handled locally in `app.tsx`
2. Everything else → `slash.exec` (runs in persistent `_SlashWorker` subprocess) → `command.dispatch` fallback

### Dev Commands

```bash
cd ui-tui
npm install       # first time
npm run dev       # watch mode (rebuilds hermes-ink + tsx --watch)
npm start         # production
npm run build     # full build (hermes-ink + tsc)
npm run typecheck # typecheck only (tsc --noEmit)
npm run lint      # eslint
npm run fmt       # prettier
npm test          # vitest
```

### TUI in the Dashboard (`hermes dashboard` → `/chat`)

The dashboard embeds the real `hermes --tui` — **not** a rewrite.  See `hermes_cli/pty_bridge.py` + the `@app.websocket("/api/pty")` endpoint in `hermes_cli/web_server.py`.

- Browser loads `web/src/pages/ChatPage.tsx`, which mounts xterm.js's `Terminal` with the WebGL renderer, `@xterm/addon-fit` for container-driven resize, and `@xterm/addon-unicode11` for modern wide-character widths.
- `/api/pty?token=…` upgrades to a WebSocket; auth uses the same ephemeral `_SESSION_TOKEN` as REST, via query param (browsers can't set `Authorization` on WS upgrade).
- The server spawns whatever `hermes --tui` would spawn, through `ptyprocess` (POSIX PTY — WSL works, native Windows does not).
- Frames: raw PTY bytes each direction; resize via `\x1b[RESIZE:<cols>;<rows>]` intercepted on the server and applied with `TIOCSWINSZ`.

**Do not re-implement the primary chat experience in React.** The main transcript, composer/input flow (including slash-command behavior), and PTY-backed terminal belong to the embedded `hermes --tui` — anything new you add to Ink shows up in the dashboard automatically. If you find yourself rebuilding the transcript or composer for the dashboard, stop and extend Ink instead.

**Structured React UI around the TUI is allowed when it is not a second chat surface.** Sidebar widgets, inspectors, summaries, status panels, and similar supporting views (e.g. `ChatSidebar`, `ModelPickerDialog`, `ToolCall`) are fine when they complement the embedded TUI rather than replacing the transcript / composer / terminal. Keep their state independent of the PTY child's session and surface their failures non-destructively so the terminal pane keeps working unimpaired.

### Electron Desktop Chat App (`apps/desktop/`)

A **separate** chat surface from both the classic CLI and the dashboard's embedded TUI. It is an Electron + React + nanostore renderer (`@assistant-ui/react`) that talks to a `tui_gateway` backend over JSON-RPC (`requestGateway(method, params)`). It does NOT embed `hermes --tui` — it has its own composer, transcript, and slash-command pipeline. Route desktop bugs to the `hermes-desktop-app-work` skill, not `hermes-dashboard-work`.

**Slash commands in the desktop app are curated client-side, then dispatched to the backend.** The pipeline:

- **Backend already provides everything.** `tui_gateway/server.py` `commands.catalog` (empty-query list) and `complete.slash` (typed-query completions) both include built-in commands, user `quick_commands`, AND skill-derived commands (`scan_skill_commands()` / `get_skill_commands()`). The desktop app does not need a new RPC to see skills.
- **The renderer curates via `apps/desktop/src/lib/desktop-slash-commands.ts`.** This is the load-bearing file. It holds `DESKTOP_COMMANDS` (the ~19 built-ins shown in the palette) plus block-lists for terminal-only / messaging-only / picker-owned / settings-owned / advanced commands that should NOT clutter the desktop popover.
  - `isDesktopSlashCommand(name)` — gates **execution**. Returns true for built-ins AND for any non-built-in (skill / quick command), so typed extension commands run.
  - `isDesktopSlashSuggestion(name)` — gates **discovery/completion**. Used by BOTH completion paths in `app/chat/composer/hooks/use-slash-completions.ts` (empty-query catalog filter + typed-query `complete.slash` filter) and by `filterDesktopCommandsCatalog`.
  - `isDesktopSlashExtensionCommand(name)` — true when the command is NOT a known Hermes built-in (i.e. a skill or user quick command). Both suggestion and catalog-filter paths allow extensions through so skill commands surface in the palette. (Added when fixing "skill commands missing from the desktop slash palette" — the curated allow-list was silently dropping every skill/quick command from completions even though they executed fine when typed.)
- **Dispatch** lives in `app/session/hooks/use-prompt-actions.ts` (`runSlash`): built-ins that the desktop owns (`/skin`, `/help`, `/new`, …) are handled locally or via `commands.catalog`; everything else goes to `slash.exec`, falling back to `command.dispatch` (which the gateway resolves into skill / alias / exec directives). A skill command resolves to `{type: "skill", message}` and is submitted as a normal prompt.

**Rule:** the desktop slash palette's curation is about hiding noise (terminal-only / messaging-only built-ins), NOT about hiding user-activated extensions. Skill commands and `quick_commands` are extensions the backend surfaces — they belong in completions. If you tighten `desktop-slash-commands.ts`, keep `isDesktopSlashExtensionCommand` flowing into both the suggestion and catalog-filter paths. Tests: `apps/desktop/src/lib/desktop-slash-commands.test.ts` (run via the repo-root `vitest`, since `apps/desktop` resolves deps from the root workspace install).

---

## Adding New Tools

Before adding any tool, settle the footprint question first (see "The
Footprint Ladder" in the Contribution Rubric): most capabilities should NOT
be core tools. For custom or local-only tools, do **not** edit Hermes core.
Use the plugin route instead: create `~/.hermes/plugins/<name>/plugin.yaml`
and `~/.hermes/plugins/<name>/__init__.py`, then register tools with
`ctx.register_tool(...)`. Plugin toolsets are discovered automatically and can be
enabled or disabled without touching `tools/` or `toolsets.py`.

Use the built-in route below only when the user is explicitly contributing a new
core Hermes tool that should ship in the base system.

Built-in/core tools require changes in **2 files**:

**1. Create `tools/your_tool.py`:**
```python
import json, os
from tools.registry import registry

def check_requirements() -> bool:
    return bool(os.getenv("EXAMPLE_API_KEY"))

def example_tool(param: str, task_id: str = None) -> str:
    return json.dumps({"success": True, "data": "..."})

registry.register(
    name="example_tool",
    toolset="example",
    schema={"name": "example_tool", "description": "...", "parameters": {...}},
    handler=lambda args, **kw: example_tool(param=args.get("param", ""), task_id=kw.get("task_id")),
    check_fn=check_requirements,
    requires_env=["EXAMPLE_API_KEY"],
)
```

**2. Add to `toolsets.py`** — either `_HERMES_CORE_TOOLS` (all platforms) or a new toolset. **This step is required:** auto-discovery imports the tool and registers its schema, but the tool is only *exposed to an agent* if its name appears in a toolset. `_HERMES_CORE_TOOLS` is not dead code — it's the default bundle every platform's base toolset inherits from.

Auto-discovery: any `tools/*.py` file with a top-level `registry.register()` call is imported automatically — no manual import list to maintain. Wiring into a toolset is still a deliberate, manual step.

The registry handles schema collection, dispatch, availability checking, and error wrapping. All handlers MUST return a JSON string.

**Path references in tool schemas**: If the schema description mentions file paths (e.g. default output directories), use `display_hermes_home()` to make them profile-aware. The schema is generated at import time, which is after `_apply_profile_override()` sets `HERMES_HOME`.

**State files**: If a tool stores persistent state (caches, logs, checkpoints), use `get_hermes_home()` for the base directory — never `Path.home() / ".hermes"`. This ensures each profile gets its own state.

**Agent-level tools** (todo, memory): intercepted by `run_agent.py` before `handle_function_call()`. See `tools/todo_tool.py` for the pattern.

---

## Dependency Pinning Policy

All dependencies must have upper bounds to limit supply-chain attack surface.
This policy was established after the litellm compromise (PR #2796, #2810) and
reinforced after the Mini Shai-Hulud worm campaign (May 2026).

| Source type | Treatment | Example |
|---|---|---|
| PyPI package | `>=floor,<next_major` | `"httpx>=0.28.1,<1"` |
| Git URL | Commit SHA | `git+https://...@<40-char-sha>` |
| GitHub Actions | Commit SHA + comment | `uses: actions/checkout@<sha>  # v4` |
| CI-only pip | `==exact` | `pyyaml==6.0.2` |

**When adding a new dependency to `pyproject.toml`:**
1. Pin to `>=current_version,<next_major` for post-1.0 (e.g. `>=1.5.0,<2`).
2. For pre-1.0 packages, use `<0.(current_minor + 2)` (e.g. `>=0.29,<0.32`).
3. Never commit a bare `>=X.Y.Z` without a ceiling — CI and reviewers will reject it.
4. Run `uv lock` to regenerate `uv.lock` with hashes.

Reference: #2810 (bounds pass), #9801 (SHA pinning + audit CI).

---

## Adding Configuration

### config.yaml options:
1. Add to `DEFAULT_CONFIG` in `hermes_cli/config.py`
2. Bump `_config_version` (check the current value at the top of `DEFAULT_CONFIG`)
   ONLY if you need to actively migrate/transform existing user config
   (renaming keys, changing structure). Adding a new key to an existing
   section is handled automatically by the deep-merge and does NOT require
   a version bump.

### Top-level `config.yaml` sections (non-exhaustive):

`model`, `agent`, `terminal`, `compression`, `display`, `stt`, `tts`,
`memory`, `security`, `delegation`, `smart_model_routing`, `checkpoints`,
`auxiliary`, `curator`, `skills`, `gateway`, `logging`, `cron`, `profiles`,
`plugins`, `honcho`.

`auxiliary` holds per-task overrides for side-LLM work (curator, vision,
embedding, title generation, session_search, etc.) — each task can pin
its own provider/model/base_url/max_tokens/reasoning_effort. See
`agent/auxiliary_client.py::_resolve_auto` for resolution order.

`curator` holds the background skill-maintenance config —
`enabled`, `interval_hours`, `min_idle_hours`, `stale_after_days`,
`archive_after_days`, `backup` (nested).

### .env variables (SECRETS ONLY — API keys, tokens, passwords):
1. Add to `OPTIONAL_ENV_VARS` in `hermes_cli/config.py` with metadata:
```python
"NEW_API_KEY": {
    "description": "What it's for",
    "prompt": "Display name",
    "url": "https://...",
    "password": True,
    "category": "tool",  # provider, tool, messaging, setting
},
```

Non-secret settings (timeouts, thresholds, feature flags, paths, display
preferences) belong in `config.yaml`, not `.env`. If internal code needs an
env var mirror for backward compatibility, bridge it from `config.yaml` to
the env var in code (see `gateway_timeout`, `terminal.cwd` → `TERMINAL_CWD`).

### Config loaders (three paths — know which one you're in):

| Loader | Used by | Location |
|--------|---------|----------|
| `load_cli_config()` | CLI mode | `cli.py` — merges CLI-specific defaults + user YAML |
| `load_config()` | `hermes tools`, `hermes setup`, most CLI subcommands | `hermes_cli/config.py` — merges `DEFAULT_CONFIG` + user YAML |
| Direct YAML load | Gateway runtime | `gateway/run.py` + `gateway/config.py` — reads user YAML raw |

If you add a new key and the CLI sees it but the gateway doesn't (or vice
versa), you're on the wrong loader. Check `DEFAULT_CONFIG` coverage.

### Working directory:
- **CLI** — uses the process's current directory (`os.getcwd()`).
- **Messaging** — uses `terminal.cwd` from `config.yaml`. The gateway bridges this
  to the `TERMINAL_CWD` env var for child tools. **`MESSAGING_CWD` has been
  removed** — the config loader prints a deprecation warning if it's set in
  `.env`. Same for `TERMINAL_CWD` in `.env`; the canonical setting is
  `terminal.cwd` in `config.yaml`.

---

## Skin/Theme System

The skin engine (`hermes_cli/skin_engine.py`) provides data-driven CLI visual customization. Skins are **pure data** — no code changes needed to add a new skin.

### Architecture

```
hermes_cli/skin_engine.py    # SkinConfig dataclass, built-in skins, YAML loader
~/.hermes/skins/*.yaml       # User-installed custom skins (drop-in)
```

- `init_skin_from_config()` — called at CLI startup, reads `display.skin` from config
- `get_active_skin()` — returns cached `SkinConfig` for the current skin
- `set_active_skin(name)` — switches skin at runtime (used by `/skin` command)
- `load_skin(name)` — loads from user skins first, then built-ins, then falls back to default
- Missing skin values inherit from the `default` skin automatically

### What skins customize

| Element | Skin Key | Used By |
|---------|----------|---------|
| Banner panel border | `colors.banner_border` | `banner.py` |
| Banner panel title | `colors.banner_title` | `banner.py` |
| Banner section headers | `colors.banner_accent` | `banner.py` |
| Banner dim text | `colors.banner_dim` | `banner.py` |
| Banner body text | `colors.banner_text` | `banner.py` |
| Response box border | `colors.response_border` | `cli.py` |
| Spinner faces (waiting) | `spinner.waiting_faces` | `display.py` |
| Spinner faces (thinking) | `spinner.thinking_faces` | `display.py` |
| Spinner verbs | `spinner.thinking_verbs` | `display.py` |
| Spinner wings (optional) | `spinner.wings` | `display.py` |
| Tool output prefix | `tool_prefix` | `display.py` |
| Per-tool emojis | `tool_emojis` | `display.py` → `get_tool_emoji()` |
| Agent name | `branding.agent_name` | `banner.py`, `cli.py` |
| Welcome message | `branding.welcome` | `cli.py` |
| Response box label | `branding.response_label` | `cli.py` |
| Prompt symbol | `branding.prompt_symbol` | `cli.py` |

### Built-in skins

- `default` — Classic Hermes gold/kawaii (the current look)
- `ares` — Crimson/bronze war-god theme with custom spinner wings
- `mono` — Clean grayscale monochrome
- `slate` — Cool blue developer-focused theme

### Adding a built-in skin

Add to `_BUILTIN_SKINS` dict in `hermes_cli/skin_engine.py`:

```python
"mytheme": {
    "name": "mytheme",
    "description": "Short description",
    "colors": { ... },
    "spinner": { ... },
    "branding": { ... },
    "tool_prefix": "┊",
},
```

### User skins (YAML)

Users create `~/.hermes/skins/<name>.yaml`:

```yaml
name: cyberpunk
description: Neon-soaked terminal theme

colors:
  banner_border: "#FF00FF"
  banner_title: "#00FFFF"
  banner_accent: "#FF1493"

spinner:
  thinking_verbs: ["jacking in", "decrypting", "uploading"]
  wings:
    - ["⟨⚡", "⚡⟩"]

branding:
  agent_name: "Cyber Agent"
  response_label: " ⚡ Cyber "

tool_prefix: "▏"
```

Activate with `/skin cyberpunk` or `display.skin: cyberpunk` in config.yaml.

---

## Plugins

Hermes has two plugin surfaces. Both live under `plugins/` in the repo so
repo-shipped plugins can be discovered alongside user-installed ones in
`~/.hermes/plugins/` and pip-installed entry points.

### General plugins (`hermes_cli/plugins.py` + `plugins/<name>/`)

`PluginManager` discovers plugins from `~/.hermes/plugins/`, `./.hermes/plugins/`,
and pip entry points. Each plugin exposes a `register(ctx)` function that
can:

- Register Python-callback lifecycle hooks:
  `pre_tool_call`, `post_tool_call`, `pre_llm_call`, `post_llm_call`,
  `on_session_start`, `on_session_end`
- Register new tools via `ctx.register_tool(...)`
- Register CLI subcommands via `ctx.register_cli_command(...)` — the
  plugin's argparse tree is wired into `hermes` at startup so
  `hermes <pluginname> <subcmd>` works with no change to `main.py`

Hooks are invoked from `model_tools.py` (pre/post tool) and `run_agent.py`
(lifecycle). **Discovery timing pitfall:** `discover_plugins()` only runs
as a side effect of importing `model_tools.py`. Code paths that read plugin
state without importing `model_tools.py` first must call `discover_plugins()`
explicitly (it's idempotent).

### Memory-provider plugins (`plugins/memory/<name>/`)

Separate discovery system for pluggable memory backends. Current built-in
providers include **honcho, mem0, supermemory, byterover, hindsight,
holographic, openviking, retaindb**.

Each provider implements the `MemoryProvider` ABC (see `agent/memory_provider.py`)
and is orchestrated by `agent/memory_manager.py`. Lifecycle hooks include
`sync_turn(turn_messages)`, `prefetch(query)`, `shutdown()`, and optional
`post_setup(hermes_home, config)` for setup-wizard integration.

**CLI commands via `plugins/memory/<name>/cli.py`:** if a memory plugin
defines `register_cli(subparser)`, `discover_plugin_cli_commands()` finds
it at argparse setup time and wires it into `hermes <plugin>`. The
framework only exposes CLI commands for the **currently active** memory
provider (read from `memory.provider` in config.yaml), so disabled
providers don't clutter `hermes --help`.

**Rule (Teknium, May 2026):** plugins MUST NOT modify core files
(`run_agent.py`, `cli.py`, `gateway/run.py`, `hermes_cli/main.py`, etc.).
If a plugin needs a capability the framework doesn't expose, expand the
generic plugin surface (new hook, new ctx method) — never hardcode
plugin-specific logic into core. PR #5295 removed 95 lines of hardcoded
honcho argparse from `main.py` for exactly this reason.

**No new in-tree memory providers (policy, May 2026):** the set of
built-in memory providers under `plugins/memory/` is closed. New memory
backends must ship as **standalone plugin repos** that users install
into `~/.hermes/plugins/` (or via pip entry points) — they implement
the same `MemoryProvider` ABC, register through the same discovery
path, and integrate via `hermes memory setup` / `post_setup()` without
landing in this tree. PRs that add a new directory under
`plugins/memory/` will be closed with a pointer to publish the
provider as its own repo. Existing in-tree providers stay; bug fixes
to them are welcome.

### Model-provider plugins (`plugins/model-providers/<name>/`)

Every inference backend (openrouter, anthropic, gmi, deepseek, nvidia, …)
ships as a plugin here. Each plugin's `__init__.py` calls
`providers.register_provider(ProviderProfile(...))` at module load.
`providers/__init__.py._discover_providers()` is a **lazy, separate
discovery system** — scanned on first `get_provider_profile()` or
`list_providers()` call, NOT by the general PluginManager.

Scan order:
1. Bundled: `<repo>/plugins/model-providers/<name>/`
2. User: `$HERMES_HOME/plugins/model-providers/<name>/`
3. Legacy: `<repo>/providers/<name>.py` (back-compat)

User plugins of the same name override bundled ones — `register_provider()`
is last-writer-wins. This lets third parties swap out any built-in
profile without a repo patch.

The general PluginManager records `kind: model-provider` manifests but does
NOT import them (would double-instantiate `ProviderProfile`). Plugins
without an explicit `kind:` get auto-coerced via a source-text heuristic
(`register_provider` + `ProviderProfile` in `__init__.py`).

Full authoring guide: `website/docs/developer-guide/model-provider-plugin.md`.

### Dashboard / context-engine / image-gen plugin directories

`plugins/context_engine/`, `plugins/image_gen/`, etc. follow the same
pattern (ABC + orchestrator + per-plugin directory). Context engines
plug into `agent/context_engine.py`; image-gen providers into
`agent/image_gen_provider.py`. Reference / docs-companion plugins
(`example-dashboard`, `strike-freedom-cockpit`, `plugin-llm-example`,
`plugin-llm-async-example`) live in the
[`hermes-example-plugins`](https://github.com/NousResearch/hermes-example-plugins)
companion repo, not in this tree.

---

## Skills

Two parallel surfaces:

- **`skills/`** — built-in skills shipped and loadable by default.
  Organized by category directories (e.g. `skills/github/`, `skills/mlops/`).
- **`optional-skills/`** — heavier or niche skills shipped with the repo but
  NOT active by default. Installed explicitly via
  `hermes skills install official/<category>/<skill>`. Adapter lives in
  `tools/skills_hub.py` (`OptionalSkillSource`). Categories include
  `autonomous-ai-agents`, `blockchain`, `communication`, `creative`,
  `devops`, `email`, `health`, `mcp`, `migration`, `mlops`, `productivity`,
  `research`, `security`, `web-development`.

When reviewing skill PRs, check which directory they target — heavy-dep or
niche skills belong in `optional-skills/`.

### SKILL.md frontmatter

Standard fields: `name`, `description`, `version`, `author`, `license`,
`platforms` (OS-gating list: `[macos]`, `[linux, macos]`, ...),
`metadata.hermes.tags`, `metadata.hermes.category`,
`metadata.hermes.related_skills`, `metadata.hermes.config` (config.yaml
settings the skill needs — stored under `skills.config.<key>`, prompted
during setup, injected at load time).

Top-level `tags:` and `category:` are also accepted and mirrored from
`metadata.hermes.*` by the loader.

### Skill authoring standards (HARDLINE)

Every new or modernized skill — bundled, optional, or contributed —
must meet these standards before merge. Reviewers reject PRs that
violate them.

1. **`description` ≤ 60 characters, one sentence, ends with a period.**
   Long descriptions bloat skill listings and dilute the model's
   attention when many skills are loaded. State the capability, not
   the implementation. No marketing words ("powerful",
   "comprehensive", "seamless", "advanced"). Don't repeat the skill
   name. Verify with:
   ```python
   import re, pathlib
   m = re.search(r'^description: (.*)$',
                 pathlib.Path('skills/<cat>/<name>/SKILL.md').read_text(),
                 re.MULTILINE)
   assert len(m.group(1)) <= 60, len(m.group(1))
   ```

2. **Tools referenced in SKILL.md prose must be native Hermes tools or
   MCP servers the skill explicitly expects.** When the skill needs a
   capability, point at the proper tool by name in backticks
   (`` `terminal` ``, `` `web_extract` ``, `` `read_file` ``,
   `` `patch` ``, `` `search_files` ``, `` `vision_analyze` ``,
   `` `browser_navigate` ``, `` `delegate_task` ``, etc.). Do NOT
   name shell utilities the agent already has wrapped — `grep` →
   `search_files`, `cat`/`head`/`tail` → `read_file`, `sed`/`awk` →
   `patch`, `find`/`ls` → `search_files target='files'`. If the skill
   depends on an MCP server, name the MCP server and document the
   expected setup in `## Prerequisites`. Anything else (third-party
   CLIs, shell pipelines, etc.) is fair game inside script files but
   should not be the headline interaction surface in the prose.

3. **`platforms:` gating audited against actual script imports.**
   Skills that use POSIX-only primitives (`fcntl`, `termios`,
   `os.setsid`, `os.kill(pid, 0)` for liveness, `/proc`, `/tmp`
   hardcoded, `signal.SIGKILL`, bash heredocs, `osascript`, `apt`,
   `systemctl`) must declare their supported platforms. Default
   posture: try to fix it cross-platform first — `tempfile.gettempdir`,
   `pathlib.Path`, `psutil.pid_exists`, Python-level filtering instead
   of `grep`. Gate to a narrower set only when the dependency is
   genuinely platform-bound.

4. **`author` credits the human contributor first.** For external
   contributions, the contributor's real name + GitHub handle goes
   first; "Hermes Agent" is the secondary collaborator. If the
   contributor's commit shows "Hermes Agent" as author (because they
   used Hermes to draft the skill), replace it with their actual name
   — credit the human, not the tool.

5. **SKILL.md body uses the modern section order.** `# <Skill> Skill`
   title, 2-3 sentence intro stating what it does and doesn't do,
   `## When to Use`, `## Prerequisites`, `## How to Run`,
   `## Quick Reference`, `## Procedure`, `## Pitfalls`,
   `## Verification`. Target ~200 lines for a complex skill,
   ~100 lines for a simple one. Cut redundant intro fluff, marketing
   prose, and re-explanations of env vars already in
   `## Prerequisites`.

6. **Scripts go in `scripts/`, references in `references/`,
   templates in `templates/`.** Don't expect the model to inline-write
   parsers, XML walkers, or non-trivial logic every call — ship a
   helper script. Reference it from SKILL.md by path relative to the
   skill directory.

7. **Tests live at `tests/skills/test_<skill>_skill.py`** and use only
   stdlib + pytest + `unittest.mock`. No live network calls. Run via
   `scripts/run_tests.sh tests/skills/test_<skill>_skill.py -q`.

8. **`.env.example` additions are isolated to a clearly delimited
   block.** Don't touch the surrounding file — contributor-supplied
   `.env.example` versions are usually stale and edits outside the
   skill's own block must be dropped during salvage.

The full salvage / modernization checklist for external skill PRs
lives in the `hermes-agent-dev` skill at
`references/new-skill-pr-salvage.md` — load it before polishing
contributor skill PRs.

---

## Toolsets

All toolsets are defined in `toolsets.py` as a single `TOOLSETS` dict.
Each platform's adapter picks a base toolset (e.g. Telegram uses
`"messaging"`); `_HERMES_CORE_TOOLS` is the default bundle most
platforms inherit from.

Current toolset keys: `browser`, `clarify`, `code_execution`, `cronjob`,
`debugging`, `delegation`, `discord`, `discord_admin`, `feishu_doc`,
`feishu_drive`, `file`, `homeassistant`, `image_gen`, `kanban`, `memory`,
`messaging`, `moa`, `rl`, `safe`, `search`, `session_search`, `skills`,
`spotify`, `terminal`, `todo`, `tts`, `video`, `vision`, `web`, `yuanbao`.

Enable/disable per platform via `hermes tools` (the curses UI) or the
`tools.<platform>.enabled` / `tools.<platform>.disabled` lists in
`config.yaml`.

---

## Delegation (`delegate_task`)

`tools/delegate_tool.py` spawns a subagent with an isolated
context + terminal session. Synchronous: the parent waits for the
child's summary before continuing its own loop — if the parent is
interrupted, the child is cancelled.

Two shapes:

- **Single:** pass `goal` (+ optional `context`, `toolsets`).
- **Batch (parallel):** pass `tasks: [...]` — each gets its own subagent
  running concurrently. Concurrency is capped by
  `delegation.max_concurrent_children` (default 3).

Roles:

- `role="leaf"` (default) — focused worker. Cannot call `delegate_task`,
  `clarify`, `memory`, `send_message`, `execute_code`.
- `role="orchestrator"` — retains `delegate_task` so it can spawn its
  own workers. Gated by `delegation.orchestrator_enabled` (default true)
  and bounded by `delegation.max_spawn_depth` (default 2).

Key config knobs (under `delegation:` in `config.yaml`):
`max_concurrent_children`, `max_spawn_depth`, `child_timeout_seconds`,
`orchestrator_enabled`, `subagent_auto_approve`, `inherit_mcp_toolsets`,
`max_iterations`.

Synchronicity rule: delegate_task is **not** durable. For long-running
work that must outlive the current turn, use `cronjob` or
`terminal(background=True, notify_on_complete=True)` instead.

---

## Curator (skill lifecycle)

Background skill-maintenance system that tracks usage on agent-created
skills and auto-archives stale ones. Users never lose skills; archives
go to `~/.hermes/skills/.archive/` and are restorable.

- **Core:** `agent/curator.py` (review loop, auto-transitions, LLM review
  prompt) + `agent/curator_backup.py` (pre-run tar.gz snapshots).
- **CLI:** `hermes_cli/curator.py` wires `hermes curator <verb>` where
  verbs are: `status`, `run`, `pause`, `resume`, `pin`, `unpin`,
  `archive`, `restore`, `prune`, `backup`, `rollback`.
- **Telemetry:** `tools/skill_usage.py` owns the sidecar
  `~/.hermes/skills/.usage.json` — per-skill `use_count`, `view_count`,
  `patch_count`, `last_activity_at`, `state` (active / stale /
  archived), `pinned`.

Invariants:
- Curator only touches skills with `created_by: "agent"` provenance —
  bundled + hub-installed skills are off-limits.
- Never deletes; max destructive action is archive.
- Pinned skills are exempt from every auto-transition and from the
  LLM review pass.
- `skill_manage(action="delete")` refuses pinned skills; patch/edit/
  write_file/remove_file go through so the agent can keep improving
  pinned skills.

Config section (`curator:` in `config.yaml`):
`enabled`, `interval_hours`, `min_idle_hours`, `stale_after_days`,
`archive_after_days`, `backup.*`.

Full user-facing docs: `website/docs/user-guide/features/curator.md`.

---

## Cron (scheduled jobs)

`cron/jobs.py` (job store) + `cron/scheduler.py` (tick loop). Agents
schedule jobs via the `cronjob` tool; users via `hermes cron <verb>`
(`list`, `add`, `edit`, `pause`, `resume`, `run`, `remove`) or the
`/cron` slash command.

Supported schedule formats:
- Duration: `"30m"`, `"2h"`, `"1d"`
- "every" phrase: `"every 2h"`, `"every monday 9am"`
- 5-field cron expression: `"0 9 * * *"`
- ISO timestamp (one-shot): `"2026-06-01T09:00:00Z"`

Per-job fields include `skills` (load specific skills), `model` /
`provider` overrides, `script` (pre-run data-collection script whose
stdout is injected into the prompt; `no_agent=True` turns the script
into the entire job), `context_from` (chain job A's last output into
job B's prompt), `workdir` (run in a specific directory with its
`AGENTS.md`/`CLAUDE.md` loaded), and multi-platform delivery.

Hardening invariants:
- **3-minute hard interrupt** on cron sessions — runaway agent loops
  cannot monopolize the scheduler.
- Catchup window: half the job's period, clamped to 120s–2h.
- Grace window: 120s for one-shot jobs whose fire time was missed.
- File lock at `~/.hermes/cron/.tick.lock` prevents duplicate ticks
  across processes.
- Cron sessions pass `skip_memory=True` by default; memory providers
  intentionally do not run during cron.

Cron deliveries are **not** mirrored into the target gateway session —
they land in their own cron session with a header/footer frame so the
main conversation's message-role alternation stays intact.

---

## Kanban (multi-agent work queue)

Durable SQLite-backed board that lets multiple profiles / workers
collaborate on shared tasks. Users drive it via `hermes kanban <verb>`;
workers spawned by the dispatcher drive it via a dedicated `kanban_*`
toolset so their schema footprint is zero when they're not inside a
kanban task.

- **CLI:** `hermes_cli/kanban.py` wires `hermes kanban` with verbs
  `init`, `create`, `list` (alias `ls`), `show`, `assign`, `link`,
  `unlink`, `comment`, `complete`, `block`, `unblock`, `archive`,
  `tail`, plus less-commonly-used `watch`, `stats`, `runs`, `log`,
  `assignees`, `heartbeat`, `notify-*`, `dispatch`, `daemon`, `gc`.
- **Worker/orchestrator toolset:** `tools/kanban_tools.py` exposes
  `kanban_show`, `kanban_complete`, `kanban_block`, `kanban_heartbeat`,
  `kanban_comment`, `kanban_create`, `kanban_link`; profiles that
  explicitly enable the `kanban` toolset outside a dispatcher-spawned
  task also get `kanban_list` and `kanban_unblock` for board routing.
- **Dispatcher:** long-lived loop that (default every 60s) reclaims
  stale claims, promotes ready tasks, atomically claims, and spawns
  assigned profiles. Runs **inside the gateway** by default via
  `kanban.dispatch_in_gateway: true`.
- **Plugin assets:** `plugins/kanban/dashboard/` (web UI) +
  `plugins/kanban/systemd/` (`hermes-kanban-dispatcher.service` for
  standalone dispatcher deployment).

Isolation model:
- **Board** is the hard boundary — workers are spawned with
  `HERMES_KANBAN_BOARD` pinned in their env so they can't see other
  boards.
- **Tenant** is a soft namespace *within* a board — one specialist
  fleet can serve multiple businesses with workspace-path + memory-key
  isolation.
- After `kanban.failure_limit` consecutive non-success attempts on the
  same task (default: 2), the dispatcher auto-blocks it to prevent spin
  loops.

Full user-facing docs: `website/docs/user-guide/features/kanban.md`.

---

## Important Policies

### Prompt Caching Must Not Break

Hermes-Agent ensures caching remains valid throughout a conversation. **Do NOT implement changes that would:**
- Alter past context mid-conversation
- Change toolsets mid-conversation
- Reload memories or rebuild system prompts mid-conversation

Cache-breaking forces dramatically higher costs. The ONLY time we alter context is during context compression.

Slash commands that mutate system-prompt state (skills, tools, memory, etc.)
must be **cache-aware**: default to deferred invalidation (change takes
effect next session), with an opt-in `--now` flag for immediate
invalidation. See `/skills install --now` for the canonical pattern.

### Background Process Notifications (Gateway)

When `terminal(background=true, notify_on_complete=true)` is used, the gateway runs a watcher that
detects process completion and triggers a new agent turn. Control verbosity of background process
messages with `display.background_process_notifications`
in config.yaml (or `HERMES_BACKGROUND_NOTIFICATIONS` env var):

- `all` — running-output updates + final message (default)
- `result` — only the final completion message
- `error` — only the final message when exit code != 0
- `off` — no watcher messages at all

---

## Profiles: Multi-Instance Support

Hermes supports **profiles** — multiple fully isolated instances, each with its own
`HERMES_HOME` directory (config, API keys, memory, sessions, skills, gateway, etc.).

The core mechanism: `_apply_profile_override()` in `hermes_cli/main.py` sets
`HERMES_HOME` before any module imports. All `get_hermes_home()` references
automatically scope to the active profile.

### Rules for profile-safe code

1. **Use `get_hermes_home()` for all HERMES_HOME paths.** Import from `hermes_constants`.
   NEVER hardcode `~/.hermes` or `Path.home() / ".hermes"` in code that reads/writes state.
   ```python
   # GOOD
   from hermes_constants import get_hermes_home
   config_path = get_hermes_home() / "config.yaml"

   # BAD — breaks profiles
   config_path = Path.home() / ".hermes" / "config.yaml"
   ```

2. **Use `display_hermes_home()` for user-facing messages.** Import from `hermes_constants`.
   This returns `~/.hermes` for default or `~/.hermes/profiles/<name>` for profiles.
   ```python
   # GOOD
   from hermes_constants import display_hermes_home
   print(f"Config saved to {display_hermes_home()}/config.yaml")

   # BAD — shows wrong path for profiles
   print("Config saved to ~/.hermes/config.yaml")
   ```

3. **Module-level constants are fine** — they cache `get_hermes_home()` at import time,
   which is AFTER `_apply_profile_override()` sets the env var. Just use `get_hermes_home()`,
   not `Path.home() / ".hermes"`.

4. **Tests that mock `Path.home()` must also set `HERMES_HOME`** — since code now uses
   `get_hermes_home()` (reads env var), not `Path.home() / ".hermes"`:
   ```python
   with patch.object(Path, "home", return_value=tmp_path), \
        patch.dict(os.environ, {"HERMES_HOME": str(tmp_path / ".hermes")}):
       ...
   ```

5. **Gateway platform adapters should use token locks** — if the adapter connects with
   a unique credential (bot token, API key), call `acquire_scoped_lock()` from
   `gateway.status` in the `connect()`/`start()` method and `release_scoped_lock()` in
   `disconnect()`/`stop()`. This prevents two profiles from using the same credential.
   See `gateway/platforms/telegram.py` for the canonical pattern.

6. **Profile operations are HOME-anchored, not HERMES_HOME-anchored** — `_get_profiles_root()`
   returns `Path.home() / ".hermes" / "profiles"`, NOT `get_hermes_home() / "profiles"`.
   This is intentional — it lets `hermes -p coder profile list` see all profiles regardless
   of which one is active.

## Known Pitfalls

### DO NOT hardcode `~/.hermes` paths
Use `get_hermes_home()` from `hermes_constants` for code paths. Use `display_hermes_home()`
for user-facing print/log messages. Hardcoding `~/.hermes` breaks profiles — each profile
has its own `HERMES_HOME` directory. This was the source of 5 bugs fixed in PR #3575.

### DO NOT introduce new `simple_term_menu` usage
Existing call sites in `hermes_cli/main.py` remain for legacy fallback only;
the preferred UI is curses (stdlib) because `simple_term_menu` has
ghost-duplication rendering bugs in tmux/iTerm2 with arrow keys. New
interactive menus must use `hermes_cli/curses_ui.py` — see
`hermes_cli/tools_config.py` for the canonical pattern.

### DO NOT use `\033[K` (ANSI erase-to-EOL) in spinner/display code
Leaks as literal `?[K` text under `prompt_toolkit`'s `patch_stdout`. Use space-padding: `f"\r{line}{' ' * pad}"`.

### `_last_resolved_tool_names` is a process-global in `model_tools.py`
`_run_single_child()` in `delegate_tool.py` saves and restores this global around subagent execution. If you add new code that reads this global, be aware it may be temporarily stale during child agent runs.

### DO NOT hardcode cross-tool references in schema descriptions
Tool schema descriptions must not mention tools from other toolsets by name (e.g., `browser_navigate` saying "prefer web_search"). Those tools may be unavailable (missing API keys, disabled toolset), causing the model to hallucinate calls to non-existent tools. If a cross-reference is needed, add it dynamically in `get_tool_definitions()` in `model_tools.py` — see the `browser_navigate` / `execute_code` post-processing blocks for the pattern.

### The gateway has TWO message guards — both must bypass approval/control commands
When an agent is running, messages pass through two sequential guards:
(1) **base adapter** (`gateway/platforms/base.py`) queues messages in
`_pending_messages` when `session_key in self._active_sessions`, and
(2) **gateway runner** (`gateway/run.py`) intercepts `/stop`, `/new`,
`/queue`, `/status`, `/approve`, `/deny` before they reach
`running_agent.interrupt()`. Any new command that must reach the runner
while the agent is blocked (e.g. approval prompts) MUST bypass BOTH
guards and be dispatched inline, not via `_process_message_background()`
(which races session lifecycle).

### Squash merges from stale branches silently revert recent fixes
Before squash-merging a PR, ensure the branch is up to date with `main`
(`git fetch origin main && git reset --hard origin/main` in the worktree,
then re-apply the PR's commits). A stale branch's version of an unrelated
file will silently overwrite recent fixes on main when squashed. Verify
with `git diff HEAD~1..HEAD` after merging — unexpected deletions are a
red flag.

### Don't wire in dead code without E2E validation
Unused code that was never shipped was dead for a reason. Before wiring an
unused module into a live code path, E2E test the real resolution chain
with actual imports (not mocks) against a temp `HERMES_HOME`.

### Tests must not write to `~/.hermes/`
The `_isolate_hermes_home` autouse fixture in `tests/conftest.py` redirects `HERMES_HOME` to a temp dir. Never hardcode `~/.hermes/` paths in tests.

**Profile tests**: When testing profile features, also mock `Path.home()` so that
`_get_profiles_root()` and `_get_default_hermes_home()` resolve within the temp dir.
Use the pattern from `tests/hermes_cli/test_profiles.py`:
```python
@pytest.fixture
def profile_env(tmp_path, monkeypatch):
    home = tmp_path / ".hermes"
    home.mkdir()
    monkeypatch.setattr(Path, "home", lambda: tmp_path)
    monkeypatch.setenv("HERMES_HOME", str(home))
    return home
```

---

## Testing

**ALWAYS use `scripts/run_tests.sh`** — do not call `pytest` directly. The script enforces
hermetic environment parity with CI (unset credential vars, TZ=UTC, LANG=C.UTF-8,
`-n auto` xdist workers, in-tree subprocess-isolation plugin). Direct `pytest`
on a 16+ core developer machine with API keys set diverges from CI in ways
that have caused multiple "works locally, fails in CI" incidents (and the reverse).

```bash
scripts/run_tests.sh                                  # full suite, CI-parity
scripts/run_tests.sh tests/gateway/                   # one directory
scripts/run_tests.sh tests/agent/test_foo.py::test_x  # one test
scripts/run_tests.sh -v --tb=long                     # pass-through pytest flags
scripts/run_tests.sh --no-isolate tests/foo/          # disable subprocess isolation (faster, for debugging)
```

### Subprocess-per-test isolation

Every test runs in a freshly-spawned Python subprocess via the in-tree plugin
at `tests/_isolate_plugin.py`. This means module-level dicts/sets and
ContextVars from one test cannot leak into the next — the historic
`_reset_module_state` autouse fixture is gone.

Implementation notes:

- The plugin uses `multiprocessing.get_context("spawn")`, which works on
  Linux, macOS, and Windows alike (POSIX `fork` is not used).
- Per-test overhead is ~0.5–1.0s (Python startup + pytest collection). xdist
  parallelism amortizes this across cores; on a 20-core box the full suite
  finishes in roughly the same wall time as before, but flake-free.
- `isolate_timeout` (configured in `pyproject.toml`) caps each test at 30s.
  Hangs are killed and surfaced as a failure report.
- Pass `--no-isolate` to disable isolation — useful when debugging a single
  test interactively, or when you specifically want to verify state leakage.
- The plugin disables itself in child processes (sentinel envvar
  `HERMES_ISOLATE_CHILD=1`), so there's no fork-bomb risk.

### Why the wrapper (and why the old "just call pytest" doesn't work)

Five real sources of local-vs-CI drift the script closes:

| | Without wrapper | With wrapper |
|---|---|---|
| Provider API keys | Whatever is in your env (auto-detects pool) | All `*_API_KEY`/`*_TOKEN`/etc. unset |
| HOME / `~/.hermes/` | Your real config+auth.json | Temp dir per test |
| Timezone | Local TZ (PDT etc.) | UTC |
| Locale | Whatever is set | C.UTF-8 |
| xdist workers | `-n auto` = all cores | `-n auto` (safe — subprocess isolation prevents cross-worker flakes) |

`tests/conftest.py` also enforces points 1-4 as an autouse fixture so ANY pytest
invocation (including IDE integrations) gets hermetic behavior — but the wrapper
is belt-and-suspenders.

### Running without the wrapper (only if you must)

If you can't use the wrapper (e.g. inside an IDE that shells pytest directly),
at minimum activate the venv. The isolation plugin loads automatically from
`addopts` in `pyproject.toml`, so you get the same per-test process isolation
either way.

```bash
source .venv/bin/activate   # or: source venv/bin/activate
python -m pytest tests/ -q
```

If you need to bypass isolation for fast feedback while debugging:

```bash
python -m pytest tests/agent/test_foo.py -q --no-isolate
```

Always run the full suite before pushing changes.

### Don't write change-detector tests

A test is a **change-detector** if it fails whenever data that is **expected
to change** gets updated — model catalogs, config version numbers,
enumeration counts, hardcoded lists of provider models. These tests add no
behavioral coverage; they just guarantee that routine source updates break
CI and cost engineering time to "fix."

**Do not write:**

```python
# catalog snapshot — breaks every model release
assert "gemini-2.5-pro" in _PROVIDER_MODELS["gemini"]
assert "MiniMax-M2.7" in models

# config version literal — breaks every schema bump
assert DEFAULT_CONFIG["_config_version"] == 21

# enumeration count — breaks every time a skill/provider is added
assert len(_PROVIDER_MODELS["huggingface"]) == 8
```

**Do write:**

```python
# behavior: does the catalog plumbing work at all?
assert "gemini" in _PROVIDER_MODELS
assert len(_PROVIDER_MODELS["gemini"]) >= 1

# behavior: does migration bump the user's version to current latest?
assert raw["_config_version"] == DEFAULT_CONFIG["_config_version"]

# invariant: no plan-only model leaks into the legacy list
assert not (set(moonshot_models) & coding_plan_only_models)

# invariant: every model in the catalog has a context-length entry
for m in _PROVIDER_MODELS["huggingface"]:
    assert m.lower() in DEFAULT_CONTEXT_LENGTHS_LOWER
```

The rule: if the test reads like a snapshot of current data, delete it. If
it reads like a contract about how two pieces of data must relate, keep it.
When a PR adds a new provider/model and you want a test, make the test
assert the relationship (e.g. "catalog entries all have context lengths"),
not the specific names.

Reviewers should reject new change-detector tests; authors should convert
them into invariants before re-requesting review.
