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AgiFlowAgiFlow/ai-plugin/skills/orchestrate/SKILL.md

orchestrate

Skill4 starsChanged 33 days agoMITView on GitHub

Pipeline orchestration: dispatch the highest-priority ready tasks/work units to agents, manage capacity, and coordinate the Todo to Done flow. Invoked as /agiflow:orchestrate. Uses list_tasks, list_active_tasks_by_org, list_members, update_task, get_work_unit_progress.

161 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use define-requirements, orchestrate-plan and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • sson0-erSkill

    define-requirements

    Work with the user, one question at a time, to complete the requirements document (docs/claudex/<slug>/01-requirements.md). Run by the orchestrator (parent). Stays out of design and implementation.

    Also in 3 projects that use this

  • EternallLightSkill

    orchestrate-plan

    Use when executing a locked, reviewed PLAN.md by delegating the implementation to visible worker agents in Orca, herdr, or cmux ONE PHASE at a time — splitting the plan into context-window-sized phases, giving every phase a pristine worker context, and (when the plan touches INDEPENDENT repos) running one worker per repo IN PARALLEL. Triggers on "run the plan with a worker", "execute the plan in the other pane", "split the plan into phases and build it with workers", "build the backend and frontend in parallel panes". Not for edits you can finish inline; outside Orca, herdr, or cmux use tgc-skills:orchestrate.

    Also in 3 projects that use this

  • sson0-erSkill

    record-evidence

    How to record external facts (docs, command output, codebase findings) as evidence and design choices as decisions. Used by the researcher, designer and reviewer agents.

    Also in 3 projects that use this

  • PinkneyJiangSkill

    improve-architecture

    扫描代码库中的架构摩擦点,识别浅模块并挖掘深模块演进机会。生成可视化交互式 HTML 诊断报告,并在用户确认后闭环实施深度重构。

    Also in 4 projects that use this

  • kjnezSkill

    ticket

    Work on a JIRA/Linear ticket end-to-end: read ticket details, explore codebase, create a branch, implement with TDD, run quality checks, update ticket status, and create a PR. Use when the user provides a ticket ID to implement. Triggers on requests like "/ticket PROJ-123", "work on this ticket", "implement PROJ-123".

    Also in 4 projects that use this

  • xfstudioSkill

    reverse-engineer

    Expert reverse engineer specializing in binary analysis,

    Also in 3 projects that use this

The file

We split this skill into the rules it gives an agent

9 rules. 0 are common, 3 are distinctive, and 6 are very specific to this project.

  • 0

    Common

    Most of the 144 edited versions we read keep these.

  • 3

    Distinctive

    This author's own choices. Worth a look.

  • 6

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Very specific:

    Do NOT implement tasks here — use /agiflow:run-task for that.

    line 24
  2. Distinctive:

    Keep capacity checks honest: do not dispatch if at capacity.

    line 25
  3. Very specific:

    Follow the shared AgiFlow project-management guidelines in references/agiflow-agents.md — agent assignment, the task status workflow and …

    line 32
  4. Very specific:

    Use list_tasks to count tasks in each active status column:

    line 42
  5. Distinctive:

    Check capacity limit (default: 3 concurrent active tasks unless specified).

    line 66
  6. Distinctive:

    If at or above capacity:

    line 67
  7. Very specific:

    Use list_tasks with status: "Todo" to retrieve the ready queue.

    line 74
  8. Very specific:

    Use /agiflow:run-task <slug> to execute it

    line 91
  9. Very specific:

    If there are any Blocked tasks, list them with their blockedReason from devInfo:

    line 96

“Common” is measured: kept by at least 6 in 10 of the 144 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Invoked as /agiflow:orchestrate. In hosts without slash-prompts, this skill is triggered by matching intent and drives AgiFlow via its MCP tools.

Usage:

  • /agiflow:orchestrate - Check pipeline state and dispatch the next highest-priority task

Guardrails

  • This is a read-assess-dispatch loop, not an implementation prompt.
  • Do NOT implement tasks here — use /agiflow:run-task for that.
  • Keep capacity checks honest: do not dispatch if at capacity.
  • Report pipeline state even when no dispatch is needed.

AgiFlow Project Management Guidelines

Follow the shared AgiFlow project-management guidelines in references/agiflow-agents.md — agent assignment, the task status workflow and transitions, work-unit best practices, and the tags strategy apply to this workflow.


Steps Track these steps as TODOs and complete them one by one.

1. Assess Current Pipeline State

  1. Use list_tasks to count tasks in each active status column:
    • status: "In Progress" — tasks currently being coded by agents
    • status: "Testing" — tasks running test suites
    • status: "Review" — tasks awaiting human review
    • status: "Blocked" — tasks requiring human intervention
    • status: "Todo" — tasks ready for pickup (sorted by priority automatically)
  2. Report the pipeline state in a concise table:
    Pipeline State:
    ┌──────────────┬───────┐
    │ Status       │ Count │
    ├──────────────┼───────┤
    │ Todo         │   N   │
    │ In Progress  │   N   │
    │ Testing      │   N   │
    │ Review       │   N   │
    │ Blocked      │   N   │
    └──────────────┴───────┘

2. Check Capacity

  1. Determine active task count: In Progress + Testing combined.
  2. Check capacity limit (default: 3 concurrent active tasks unless specified).
  3. If at or above capacity:
    • Report: "At capacity (N active tasks). No dispatch needed."
    • List any Blocked tasks that need human attention.
    • Stop here.

3. Prioritize the Todo Queue

  1. Use list_tasks with status: "Todo" to retrieve the ready queue.
    • Tasks are automatically sorted by priority (high → medium → low).
    • Within the same priority, tasks are ordered by position then creation date.
  2. Review the top candidates:
    • Show the top 3-5 Todo tasks with: slug, title, priority, assignee, retryCount (from devInfo)
    • Skip any task where devInfo.retryCount >= devInfo.maxRetries (should be Blocked — flag it)

4. Dispatch

  1. Pick the highest-priority eligible Todo task.
  2. Report the dispatch decision:
    Dispatching: [SLUG] Task title (priority: high)
    Reason: Highest priority task in Todo queue
  3. Instruct the agent to run the task:
    • Use /agiflow:run-task <slug> to execute it
    • Or if already in an agent session, invoke the run-task prompt directly

5. Surface Blocked Tasks

  1. If there are any Blocked tasks, list them with their blockedReason from devInfo:
    Blocked Tasks Requiring Human Attention:
    - [SLUG] Task title: <blockedReason>
  2. Suggest actions for each blocked task (e.g., resolve dependency, provide credentials, clarify spec).

Common Mistakes to Avoid

  • ❌ Dispatching when already at capacity
  • ❌ Picking a lower-priority task when a higher-priority Todo exists
  • ❌ Dispatching a task that has retryCount >= maxRetries (it should be Blocked)
  • ❌ Skipping the pipeline state report
  • ❌ Attempting to implement the task inside this prompt

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