Issue #5 (Python core migration, CAS state transitions, shadow watcher, auto-completion gate, eager-import immutable runtime, B-13 freeze removal) is complete and merged to main. This stamps the release. SemVer: MINOR, not MAJOR. The change is large but breaks nothing. Across the whole Issue #5 range there are zero file deletions and zero renames, the event wire schema stays at SCHEMA_VERSION 1, all four literal script paths survive as compatibility shims, the 968-line legacy shell loop is still in run_loop.sh, and every default change reverts through a single environment variable (MAM_DELEGATION_PY / MAM_ENGINE_CAS / MAM_LOOP_PY / MAM_LOOP_FREEZE). The riskiest new feature, auto-completion, ships default-off. No operator has anything to migrate, which is the decisive reason not to call it 5.0.0. The reasoning is recorded in the VERSIONS.md release notes, not just here. Close a gap in the lockstep guard. lib.sh exports MAM_VERSION and eager_load() refuses to start the loop when it disagrees with FRAMEWORK_VERSION, so eager.py is a load-bearing fourth leg — but test_version_consistency.py only checked three, and the sole check on eager.py was a hardcoded literal in the phase 4 test that a release bump has to edit anyway. The lockstep test now covers eager.py, a new test pins the fail-closed gate itself, and the phase 4 test no longer carries a version literal. Fix a latent test-isolation defect the bump exposed. The first full run failed four tests with "MAM_VERSION mismatch: expected 4.4.0, got 4.3.0 in environment" — 4.3.0 was not in the tree, it was inherited from the shell that launched pytest and had sourced the pre-bump lib.sh. Those tests were measuring the runner's shell rather than the tree under test, and only passed until now because the two values always happened to agree. A session-scoped fixture drops the ambient value. Production is unaffected: run_loop.sh:17 sources lib.sh before anything else and lib.sh re-exports MAM_VERSION unconditionally, so a stale inherited value is always overwritten before Python starts. Full suite: 750 passed in 912.50s, 0 failed, 0 skipped. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01UrDNJkHmm18uu7n7JwV5Qd
139 lines
8.2 KiB
Markdown
139 lines
8.2 KiB
Markdown
---
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name: multi-agent-mux-delegate-job
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description: "Delegate a unit of work to any autonomous agent (claude-code, hermes, agy, grok-build, codex, or a human) and observe it asynchronously over an MQTT event channel. Supported roles include orchestrator, worker, and reviewer."
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version: 4.4.0
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author: godopu
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license: MIT
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platforms: [linux, macos, windows]
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environments: [terminal, herdr]
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metadata:
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hermes:
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tags: [agent, herdr, multi-agent, delegate, mqtt, async, job]
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related_skills: [multi-agent-mux-create, multi-agent-mux-resume, multi-agent-mux-loop]
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prereq_skills: [multi-agent-mux-create]
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---
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# multi-agent-mux-delegate-job — Async Job Delegation over MQTT
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Delegate a unit of work to any autonomous agent, then **observe** it asynchronously instead of blocking. Every job gets a unique ID and a registry record. The worker agent publishes lifecycle events (`started`, `permission_required`, `progress`, `completed`, `error`) to a per-job MQTT topic, and the delegator/orchestrator subscribes to verify the final state.
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This skill allows any agent (`claude-code`, `hermes`, `agy`, `grok-build`, etc.) to play any role: **Orchestrator/Delegator**, **Worker/Implementer**, or **Reviewer**.
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---
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## Roles in Multi-Agent Mux
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- **Orchestrator (Delegator)**: Initiates the job, coordinates other agents, handles loops and reviews, and commits final changes.
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- **Worker (Implementer)**: Receives the brief file or task prompt, performs the implementation, and emits started/completed/error events.
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- **Reviewer**: Evaluates git diffs or artifacts produced by the worker, and responds with a `completed` event containing `"PASS"` or feedback.
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---
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## Core Commands (CLI)
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The `multi-agent-mux-delegate-job` bash wrapper handles job registration, subscriber management, agent session targeting, and validation hooks:
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```bash
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# 1) Submit a new job to a targeted agent session (e.g. herdr session name 'demo')
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multi-agent-mux-delegate-job submit \
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--agent <claude-code|hermes-agent|agy-agent|grok-build|human> \
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--agent-session herdr:<session_name> \
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--prompt "Task description or instructions here" \
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--role <Worker|Planner|Reviewer> \
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--timeout 3600 --idle-timeout 120
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# 2) Submit a job with a feedback loop (Worker-Reviewer Loop)
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multi-agent-mux-delegate-job submit \
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--agent <worker_agent> --agent-session herdr:<worker_session> \
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--type loop --reviewer <reviewer_agent> --reviewer-session herdr:<reviewer_session> \
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--prompt "Task description"
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# 3) Check job status and audit logs
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multi-agent-mux-delegate-job status --job <JOB_ID>
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multi-agent-mux-delegate-job logs <JOB_ID> # Chronological log of events
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multi-agent-mux-delegate-job list # Summary of all registered jobs
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# 4) Verify job artifacts with a validation script
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multi-agent-mux-delegate-job verify --job <JOB_ID> --validate ./validate.sh
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```
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---
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## Task Delegation Types
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Supported job types include:
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- `direct` (default): Single agent execution (direct tasking).
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- `loop` (Worker-Reviewer Loop): Alternates worker execution and reviewer evaluation until reviewer approves (`PASS`) or iterations run out.
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- `discuss` (Research & Discussion): Collaboration between two agents to reach a consensus (e.g., agreeing on a design or plan).
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For detailed state machine diagrams and configurations, see [DELEGATION_TYPES.md](./DELEGATION_TYPES.md).
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---
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## Where the Implementation Lives (v4.3.0)
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The implementation moved to the `lib_py.delegation` package in issue #5 phase 1.
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`scripts/{mqtt_common,registry,publish_event,job_subscriber}.py` remain as
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compatibility shims and **their paths are unchanged** -- every command in this
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document still works verbatim. Each shim binds the `lib_py.delegation` package
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to the tree next to itself, once per process, without touching `sys.path`, so
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`import mqtt_common` yields the same module object as
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`lib_py.delegation.mqtt_common`.
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Which tree wins, by execution context:
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| Context | Resolved by | Tree that wins |
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| Loop process and its children (frozen `lib.sh` sourced) | the helper's explicit bootstrap from `SKILL_DIR` | the frozen snapshot |
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| Agent session running a **frozen** script path while `PYTHONPATH` still points live | the shim, from its own location | the frozen snapshot (B-13 preserved) |
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| Live helpers (create/stop/resume/reconcile) | `PYTHONPATH` or the shim (same tree) | the live tree |
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| Standalone, no `PYTHONPATH` | the shim's fallback append | the shim's own tree |
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`lib.sh` calls the package through `_delegation_py`, which inserts its own
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`SKILL_DIR` at the front of the import path. It deliberately does **not** use
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`python -m`: for `-m` the current directory precedes `PYTHONPATH`, so a frozen
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loop whose working directory happened to contain a `lib_py` package would have
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silently executed live code. The working directory is left untouched, because
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the registry and audit-log paths are relative to it.
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Setting `MAM_DELEGATION_PY=0` switches the shell helpers back to their preserved
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legacy bodies with no redeploy.
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One in-process caveat: the package binds once per process and is never rebound,
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so do not import a frozen shim after a live `lib_py.delegation` is already bound
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inside the same interpreter. Production never does this — each delegated job is
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a fresh interpreter — but a test harness could.
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---
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## The Event Protocol Contract
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Every agent participating in the delegation contract must follow the same lifecycle publishing protocol using `publish_event.py`:
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1. **On Start**: Publish `started` event.
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`python3 .agents/skills/multi-agent-mux-delegate-job/scripts/publish_event.py --job "$JOB_ID" --event started`
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2. **On Tool/Permission Prompt**: Publish `permission_required` event.
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`python3 ... --job "$JOB_ID" --event permission_required --detail "<tool>:<reason>"`
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3. **On Progress Update (Optional)**: Publish `progress` event.
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`python3 ... --job "$JOB_ID" --event progress --detail "<status_update>"`
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4. **On Success**: Publish `completed` event.
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`python3 ... --job "$JOB_ID" --event completed --detail "<summary>"` (Reviewer should include `"PASS"` in the detail to approve).
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5. **On Failure/Feedback**: Publish `error` event.
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`python3 ... --job "$JOB_ID" --event error --detail "<reason_or_feedback>"`
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---
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## Audit Logs
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Job lifecycle execution events are persistently mirrored to an append-only log under `.mam/delegate_job_logs/<job_id>/` (containing `meta.json`, `events.ndjson`, and `status.json`). Use `multi-agent-mux-delegate-job logs <job_id>` to view the timeline.
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---
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## Best Practices and Pitfalls
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- **Subscribe-Before-Publish**: The subscriber must be running before the agent starts publishing. The `submit` command handles this automatically by launching the subscriber in the background first.
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- **Fresh job_id Propagation**: Make sure the worker agent receives the correct `JOB_ID` generated for the current run, rather than reusing stale IDs from previous sessions.
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- **Brief delivery via file path**: For long or complex prompts, write the instructions to a file (e.g. `/tmp/task-brief.md`) and pass a short prompt pointing to the file path to prevent terminal buffer overflows.
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- **Prompts injected into a live agent session MUST be English, ASCII-only, and short** — this is exactly what `--prompt`/the `instructions` string sent to `run_agent()` end up as. Any Korean (or other non-ASCII) content the task needs to convey must go in a markdown brief file (e.g. `.mam/jobs/<id>/brief.md`, written in Korean is fine) that the injected prompt merely tells the agent to read. Two independent bugs in `send_keys_safe`'s paste-verification (in `lib.sh`) made this matter in practice: (a) its marker was taken with a byte-based `tail -c 24`, which can slice a multi-byte UTF-8 (e.g. Korean) character in half; (b) the rendered pane soft-wraps long lines at the terminal width, which can split the marker across two visual lines. Both are now fixed at the source (character-safe truncation + newline-stripped matching before comparison), but keeping injected prompts short/English/file-referencing is still the cheapest way to avoid ever exercising this edge case at all — it's also simply what `submit`'s own default instruction template already does (see `Core Commands` above).
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- **Batch Grouping**: Group non-overlapping tasks into batches to parallelize execution across multiple agent sessions, reducing overhead.
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