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project-management

Manage a project’s execution plan and lifecycle across multiple agents. Track task dependencies or repeated work cycles, identify tasks ready to start, handle pauses and completion, and prepare project status reports and final results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

원문원문 설명 보기

Use before any projectflow call or Team Leader workflow involving Project state, Project lifecycle, DAG planning, Loop planning, ready node checks, pause/resume/complete, project recovery, heartbeat project checks, or project-level result aggregation. Always use team-coordination first when the question is how to organize the work.

설치 방법 보기

이럴 때 유용합니다

  • Managing plans with task dependencies
  • Tracking repeated work cycles
  • Pausing and resuming projects
  • Preparing project status reports

포함된 파일(2)

  • SKILL.md13.7 KB
  • references/dag-execution.md3.1 KB

SKILL.md(원문)

설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.

Project Management

You manage Project files, Project lifecycle, and Project execution plans. Use this skill as the Project state layer. Use team-coordination to decide the strategy, and use task-management to delegate or check individual Worker tasks.

Project state is tool-owned. Do not create, edit, delete, or repair shared/projects/** with shell commands, heredocs, direct file writes, rm, mkdir, cp, or Python module execution. Use projectflow actions only. If projectflow fails or returns inconsistent state, stop and report the blocker instead of manually patching files.

Scope

Use this skill for:

  • projectflow calls
  • Project metadata and lifecycle state
  • DAG and Loop execution plans
  • ready-node resolution
  • Project pause, resume, and completion
  • heartbeat and recovery checks
  • Project-level result aggregation

Do not use this skill to decide whether the work should be DAG or Loop; use team-coordination first. Do not use this skill to create Worker task files or check result.md; use task-management.

Project Files

Project files live under:

shared/projects/{project-id}/

Use:

  • meta.json for Project metadata and lifecycle status
  • plan.md for the current execution plan
  • result.md for the final Project result

The execution plan type is stored in plan.md as **Plan Type**: dag or **Plan Type**: loop. Do not put Project lifecycle status in plan.md. Do not hand-edit meta.json.status; use projectflow.

Use filesync before reading remote Project files and after changing local Project files. Use directory paths with a trailing slash, such as shared/projects/{project-id}/. projectflow reads and writes local shared files only.

If pulling shared/projects/{project-id}/ fails, stop before any Project state mutation. Do not pull only meta.json or plan.md and continue to mark nodes, resolve ready nodes, record Loop iterations, or complete the Project.

IDs

Use safe IDs only. Project and task IDs must match:

[A-Za-z0-9_-]+

Use these formats:

  • projectId: {short-description}-YYYYMMDD-HHMMSS
  • DAG task ID: {projectId}-{seq}
  • Loop task ID: {projectId}-i{iteration}-{seq}

Do not use colons, dots, slashes, spaces, or short standalone IDs such as st-01.

Projectflow Actions

Use projectflow for:

  • create_project
  • plan_dag
  • ready_nodes
  • plan_loop
  • ready_loop_nodes
  • record_loop_iteration
  • pause_project
  • resume_project
  • complete_project

projectflow does not push or pull files. It also does not send Matrix messages, stop Workers, accept task results, or write Worker task specs.

Create Project

Create the Project before planning DAG or Loop work:

{
  "action": "create_project",
  "payload": {
    "projectId": "{project-id}",
    "title": "{title}",
    "source": "{optional source}",
    "requester": "{requester Matrix id or room marker}",
    "parentTaskId": "{optional parent task id}"
  }
}

This creates meta.json and an initial DAG plan.md. After creation, publish shared/projects/{project-id}/.

Lifecycle

Lifecycle actions only change Project lifecycle state. They do not change the graph, accept task results, resolve ready nodes, delegate work, stop Workers, or aggregate final output.

Pause:

  1. Use only after team-coordination has selected a pause or interruption path, or when a recovery path needs to close scheduling.
  2. Run projectflow(action="pause_project").
  3. Publish shared/projects/{project-id}/.
  4. Do not issue new work while paused.

Resume:

  1. Confirm the requester explicitly wants scheduling to continue.
  2. Pull shared/projects/{project-id}/.
  3. Run projectflow(action="resume_project").
  4. Publish shared/projects/{project-id}/.
  5. Continue through normal result checking, plan refresh if needed, and ready-node resolution.

Complete:

  1. Confirm delivery criteria are satisfied.
  2. Write shared/projects/{project-id}/result.md.
  3. Run projectflow(action="complete_project").
  4. Publish shared/projects/{project-id}/.
  5. Report the final result to the requester recorded on the Project.

DAG Operations

Use DAG when team-coordination decided the work is finite and dependencies can be planned now.

plan_dag receives the complete graph you want to keep:

{
  "action": "plan_dag",
  "payload": {
    "projectId": "{project-id}",
    "tasks": [
      {
        "taskId": "{project-id}-01",
        "title": "Short outcome title",
        "assignedTo": "<matrix-localpart>",
        "dependsOn": []
      }
    ]
  }
}

Each node uses:

  • taskId
  • title
  • assignedTo
  • dependsOn

For assignedTo, use the Worker's Matrix localpart (the part between @ and : in matrixUserID). Extract it mechanically — never guess, strip, or transform.

Lookup steps (mandatory before every plan_dag / plan_loop call):

  1. Run agt get workers --team "$TEAM_CR" -o json
  2. For each Worker, extract the localpart from .matrixUserID: e.g. @worker-issue-resolver:domain → worker-issue-resolver
  3. Use that localpart verbatim as assignedTo

❌ Do NOT use CLI .name field directly (it may include deployment prefixes like magic-cn-...-worker-issue-resolver) ❌ Do NOT strip prefixes yourself — you will incorrectly remove legitimate name components ❌ Do NOT infer worker names from memory, AGENTS.md, or display names

CLI .namematrixUserID✅ assignedTo❌ Wrong
magic-cn-x0a4t4pr201-worker-issue-resolver@worker-issue-resolver:domainworker-issue-resolverissue-resolver
magic-cn-plt4s29va0r-worker-dev-worker@dev-worker:domaindev-workerworker

Do not use worker, owner, dependencies, or standalone short IDs.

When you call plan_dag, send the full graph you want to keep:

  • keep accepted nodes that still matter
  • omit obsolete nodes
  • add new nodes for changed scope, fixes, verification, or follow-up work

plan_dag preserves existing node status for nodes with the same taskId. It does not resume a paused Project, accept task results, or delegate work.

Call ready_nodes only when the Project is active. It returns pending DAG nodes whose dependencies are satisfied by accepted [x] nodes. Delegate returned nodes with task-management.

See references/dag-execution.md for DAG node and dependency design.

Loop Operations

Use Loop when team-coordination decided the work should repeat until a stop condition, quality gate, evidence threshold, or maximum iteration count.

plan_loop receives the complete Loop plan you want to keep:

{
  "action": "plan_loop",
  "payload": {
    "projectId": "{project-id}",
    "goal": "{loop goal}",
    "stopCondition": "{condition for stopping}",
    "iterationTemplate": "{how each iteration should run}",
    "maxIterations": 5,
    "currentIteration": 1,
    "tasks": [
      {
        "taskId": "{project-id}-i001-01",
        "title": "Short outcome title",
        "assignedTo": "<matrix-localpart>",
        "dependsOn": []
      }
    ]
  }
}

Required Loop inputs:

  • goal
  • stopCondition
  • iterationTemplate
  • maxIterations

Optional inputs:

  • currentIteration
  • status
  • tasks

For every Loop task, assignedTo follows the same rule as DAG tasks: extract the Matrix localpart from agt get workers output. Never strip or transform.

Use ready_loop_nodes to find pending nodes in the current iteration whose dependencies are satisfied by accepted [x] nodes. Delegate returned nodes with task-management.

After evaluating an iteration, use record_loop_iteration:

{
  "action": "record_loop_iteration",
  "payload": {
    "projectId": "{project-id}",
    "iteration": 1,
    "decision": "continue",
    "summary": "{what you learned}",
    "nextAction": "{optional next step}"
  }
}

Allowed decisions:

  • continue
  • replan
  • ask_user
  • stop_success
  • stop_blocked

record_loop_iteration records your decision and updates Loop status. It does not create the next iteration's tasks by itself; call plan_loop when you need a new current-iteration task set.

Result Gate

When a Worker result arrives:

  1. Use task-management to pull and check the task result.
  2. Pull shared/projects/{project-id}/.
  3. Read Project meta.json and plan.md.
  4. If the Project is paused, stop. Do not accept results, mark [x], resolve ready nodes, or delegate work.
  5. If active, use team-coordination to decide whether to accept, verify, repair, replan, ask the requester, continue Loop, or complete.

Only accepted [x] plan nodes satisfy dependencies for ready_nodes and ready_loop_nodes. A Worker SUCCESS is not enough by itself.

After you accept a DAG or Loop task result, update the corresponding plan node to [x], publish Project files, then resolve ready nodes. Use the Project Status Reports template below for the report content, then use communication to deliver it to the requester.

Project Status Reports

Build Project status report content here because it describes Project execution state. Use communication only for routing, target room, @mention, and same-room versus cross-room delivery.

Before writing a requester report:

  1. Pull and read shared/projects/{project-id}/meta.json and plan.md.
  2. Identify the plan type from plan.md.
  3. For DAG, report graph progress through dependencies and next ready waves.
  4. For Loop, report iteration progress through the current iteration, iteration decision, and next iteration path.
  5. Write the report in the language selected by AGENTS.md Response Language, then use communication to deliver it to the requester recorded on the Project.

Status emoji for task and Project state. Keep the emoji stable, but localize the visible state label to the report language:

StateEmoji
Completed✅
In Progress🔄
Pending⏳
Blocked❌
Revision🔁

Keep the report envelope consistent across DAG and Loop:

---

## <localized project status report heading>

**<localized project name label>**: <name>
**<localized project ID label>**: <project-id>
**<localized execution mode label>**: <DAG or Loop>
**<localized project status label>**: <emoji + localized state label>
**<localized current focus label>**: <DAG wave/current node, or Loop iteration n / max and topic>

**<localized summary label>**: <1-3 sentences about what changed and what happens next>

**<localized task status label>**:
| <localized task ID label> | <localized task title label> | <localized owner label> | <localized status label> | <localized context label> |
|---|---|---|---|---|
| <task-id> | <title> | <worker> | <emoji + localized state label> | <dependencies, iteration role, result note, or -> |

**<localized execution progress label>**:
```
<DAG dependency flow or Loop iteration line; choose the matching shape below>
```

**<localized deliverables label>**:
- `<path>` - <what it contains>

**<localized next steps label>**:
1. <next DAG transition, next Loop decision, or requester action>

**<localized notes label>**: <blocker, risk, or decision needed; omit section if none>

Use this execution progress shape for DAG reports:

<task-id> <emoji> -> <task-id> <emoji> -> <task-id> <emoji>
                         ^
<task-id> <emoji> -------|

Use the DAG progress section to show the dependency path that changed, newly unblocked nodes, or the next ready wave. If the graph is large, show only the relevant changed path and summarize the rest in the task table.

Use this execution progress shape for Loop reports:

Iteration 1 ✅ -> Iteration 2 🔄 -> Iteration 3 ⏳ ... Max <n>
                  Current: <current iteration topic>
                  Decision: <continue, replan, ask_user, stop_success, stop_blocked, or pending evaluation>

Use the Loop progress section to show current iteration number, maximum iterations, current iteration topic, and the latest Leader decision. Do not present future Loop rounds as if they were pre-planned DAG tasks. Show only the current iteration's task statuses in the task table unless prior iteration context is necessary.

For intermediate updates, include the Project header, summary, task status table, and next steps. Omit the deliverables section unless new deliverables are available, and omit the execution progress section only when neither DAG flow nor Loop iteration state changed.

Heartbeat And Recovery

Do not call check_active_tasks for now.

Team Leader heartbeat is temporarily disabled. Follow HEARTBEAT.md: do not probe Worker runtime, inspect active tasks, or send anomaly reports from scheduled heartbeat runs.

Worker runtime probes are disabled because Kubernetes Team Workers currently have no per-Worker Service. Hostname probes such as http://agentteams-worker-<worker>:8088/api/chats can misreport healthy Workers as unreachable.

For recovery, act only on explicit room messages, requester instructions, or Project files you were directly asked to inspect.

References

Read only when needed:

  • references/dag-execution.md - DAG input shape, node design, dependency design, dynamic replanning, and ready nodes.

Patch Rules

Do not:

  • treat task status as Project lifecycle state
  • continue dispatching while the Project is paused
  • use plan_dag or plan_loop as a substitute for resume_project
  • use lifecycle actions as the whole pause, stop, or interruption workflow
  • call ready-node resolution before pulling current Project files

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