# Custodian Agent Runtime — v0.1

Single-pass OODA agent loop. Observes project state via the State Hub, reasons
about it with an LLM, and executes bounded write operations.

## Architecture

```
agent.py          CLI entry point + OODA orchestrator
context.py        Observe: fetch state-hub data + build LLM context prompt
actions.py        Act: execute sanctioned write operations
prompts/          System prompt templates (future)
policies/         Agent-level policies (future)
tool_adapters/    Additional MCP/API tool adapters (future)
tests/            Unit tests (offline, no live API required)
```

See `canon/architecture/adr-002-custodian-agent-runtime-design.md` for
all architectural decisions.

## OODA Loop

```
Observe  →  fetch_state(domain)           # HTTP GET /state/summary or /state/domain/{slug}
Orient   →  load_constitution()           # reads canon/constitution/
             build_context(state, const)  # assembles LLM prompt
Decide   →  LLM call via llm-connect      # returns markdown + JSON action plan
Act      →  parse_plan(response)          # extract JSON block
             execute(plan)                # run sanctioned writes
```

## Sanctioned Write Operations (ADR-002 D4)

Only three operations may be executed without human approval:

| Operation | State-hub endpoint | Reversible |
|---|---|---|
| `add_progress_event` | `POST /progress/` | Yes (append-only log) |
| `update_task_status` | `PATCH /tasks/{id}/` | Yes |
| `flag_for_human` | `PATCH /tasks/{id}/` | Yes (clear with `clear_human_flag`) |

## Prerequisites

- State-hub running: `cd state-hub && make api`
- LLM available: `claude` CLI in PATH (for default `claude-code` provider)
  or set `OPENROUTER_API_KEY` / `GEMINI_API_KEY` for other providers

## Install

```bash
cd runtime
uv sync
```

## Usage

```bash
cd runtime

# Focus on custodian domain (cheaper — ~10% of full summary tokens)
uv run python agent.py --domain custodian

# Full cross-domain view
uv run python agent.py --all

# Preview actions without executing
uv run python agent.py --domain custodian --dry-run

# Use a different LLM provider
uv run python agent.py --domain custodian --llm gemini
uv run python agent.py --domain custodian --llm openrouter

# Custom state-hub URL
uv run python agent.py --domain custodian --api-base http://10.0.0.5:8000
```

## Output

The agent prints a trace to stdout:

```
[custodian-agent] 2026-03-12T20:00:00 scope=domain=custodian
[observe] fetching state from state-hub…
[orient] loading constitution and building context…
[decide] calling LLM via provider='claude-code'…
[act] executing plan (live): 1 events, 0 task updates, 0 flags
  ✓ add_progress_event: 'Reviewed custodian domain: 2 active workstreams…'
[custodian-agent] done — 1 actions.
```

The LLM's reasoning trace is saved to `memory/working/agent-session-{ts}-{scope}.md`.

## Tests

```bash
cd runtime
uv run pytest -v
```

All 32 tests run offline (no live state-hub, no LLM API key required).

## Extending

- **New observations**: extend `build_context()` in `context.py`
- **New actions**: add to `actions.py` and update `SANCTIONED_ACTIONS` — but
  any expansion of the action surface requires a new ADR and human approval
  (see constitution §2–§4)
- **Tool adapters**: add to `tool_adapters/` following the llm-connect
  `LLMAdapter` pattern