agent-loop-ext
Crash-resilient external agent loop with state persistence and CI/CD integration
Orchestrate multi-loop background operations via the Mission Control dashboard — start sessions, dispatch missions, monitor, and stop
$ npx -y skills add jmagly/aiwg --skill mission-control --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/mission-controlContext preview
The summary Claude sees to decide when to auto-load this skill.
Orchestrate multi-loop background operations via the Mission Control dashboard — start sessions, dispatch missions, monitor, and stop
namespace: aiwg name: mission-control platforms: [all] description: Orchestrate multi-loop background operations via the Mission Control dashboard — start sessions, dispatch missions, monitor, and stop
You orchestrate multi-loop background operations using the Mission Control dashboard.
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
| Pattern | Example | Action | |---------|---------|--------| | Background tasks | "run these tasks in the background" | Start session + dispatch | | Parallel orchestration | "orchestrate X and Y in parallel" | Start session + dispatch each | | Monitor loops | "monitor background tasks" | `aiwg mc status` or `aiwg mc watch` | | Start session | "start a mission control session" | `aiwg mc start` | | Check status | "how are the background tasks doing?" | `aiwg mc status --json` | | Stop missions | "stop background work" | `aiwg mc stop` |
When triggered:
1. **Determine intent**:
2. **For new background orchestration** — Mission Control has a four-step lifecycle: start → dispatch → **run** → status. Missions stay `queued` until `mc run` launches them as ralph loops; status syncs back to mc.session.json automatically when `mc status` or `mc watch` is called.
Apply the LFD loop-control contract before dispatching long-running or eval-driven missions:
mechanical verifier; self-report is secondary evidence.
where the surface can observe them. Budget exhaustion stops the mission and emits a best-output report instead of continuing randomly.
diagnostic, and structural variant for each retry cycle.
within the configured exploration quota.
VOID to workers; keep holdout answers and detailed lint diagnostics outside optimizer-readable mission output.
# 1. Start a named session (creates the state file) aiwg mc start --name "Sprint 4 Construction" # 2. Dispatch missions (queues them — does NOT execute) # --completion is REQUIRED; `mc run` will skip missions without one. # --max-iterations N caps ralph iterations per mission (default: 10). # Optional LFD hard stops: --max-total-tokens, --max-output-tokens, # --max-tool-calls, --max-total-cost, --max-wall-clock-minutes, # --exploration-quota. aiwg mc dispatch <session-id> "Fix auth service" --completion "npm test passes" --priority high --max-iterations 50 --max-total-tokens 50000 --exploration-quota 3 aiwg mc dispatch <session-id> "Add pagination" --completion "all list endpoints paginated" aiwg mc dispatch <session-id> "Write integration tests" --completion "coverage > 80%" --max-iterations 25 # 3. RUN — drains the queue by launching each mission as a detached ralph # loop. Without this step missions sit in QUEUED forever (#1439). aiwg mc run <session-id> # 4. Monitor — `mc status` polls each ralph loop's session-state.json and # syncs progress back to mc (queued → running → done|failed|aborted). aiwg mc status <session-id> aiwg mc watch <session-id>
3. **For monitoring**:
# Dashboard view aiwg mc status # Machine-readable for agent orchestration aiwg mc status --json # List all sessions aiwg mc list
4. **For lifecycle management**:
# Pause all running missions aiwg mc pause <session-id> # Resume paused session aiwg mc resume <session-id> # Stop (abort all) aiwg mc stop <session-id> # Stop (let running missions finish, cancel queued) aiwg mc stop <session-id> --drain
5. **Report the result** inline — summarize session state and mission progress.
**User**: "Run these three features in parallel: auth fix, pagination, and test coverage"
**Action**:
aiwg mc start --name "Parallel Features" aiwg mc dispatch <id> "Fix auth service" --completion "auth tests pass" aiwg mc dispatch <id> "Add pagination to list endpoints" --completion "paginated responses" aiwg mc dispatch <id> "Increase test coverage" --completion "coverage > 80%"
**Response**: "Started Mission Control session 'Parallel Features' with 3 missions queued. Use `aiwg mc status` to monitor progress."
**User**: "How are the background tasks doing?"
**Action**:
aiwg mc status
**Response**: "Mission Control 'Parallel Features': 1/3 done, 2 running (auth fix complete, pagination at loop 3/10, coverage at loop 2/10)."
**User**: "Stop the background tasks, let running ones finish"
**Action**:
aiwg mc stop <session-id> --drain
**Response**: "Draining session: 1 queued mission cancelled, 2 running missions will complete naturally."
If the user's intent is ambiguous:
Reusable project context and specialist workflows for the AI tools you already use. Plan software, coordinate specialist reviews, prepare campaigns, investigate incidents, organize research, curate media, and maintain operational knowledge.
Repo: jmagly/aiwg
Crash-resilient external agent loop with state persistence and CI/CD integration
Detect requests for iterative autonomous agent loops and route to the appropriate loop executor
Automatically execute tests when code-generating agents modify source files, enforcing the execute-before-return pattern
Enable agent loops to learn from similar past tasks and share patterns across loops
Query and manage the executable feedback debug memory
Execute tests on generated code and iterate until passing