orchestrate
SkillProductivityPipeline 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the orchestrate skill
What this skill tells your AI
The instructions your AI receives, as published by hashgraph-online/awesome-codex-plugins in plugins/AgiFlow/ai-plugin/skills/orchestrate/SKILL.md and read by ahel’s review.
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-taskfor 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
-
Use
list_tasksto count tasks in each active status column:status: "In Progress"— tasks currently being coded by agentsstatus: "Testing"— tasks running test suitesstatus: "Review"— tasks awaiting human reviewstatus: "Blocked"— tasks requiring human interventionstatus: "Todo"— tasks ready for pickup (sorted by priority automatically)
-
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
- Determine active task count:
In Progress+Testingcombined. - Check capacity limit (default: 3 concurrent active tasks unless specified).
- 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
-
Use
list_taskswithstatus: "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.
-
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
- Pick the highest-priority eligible Todo task.
- Report the dispatch decision:
Dispatching: [SLUG] Task title (priority: high) Reason: Highest priority task in Todo queue - 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
- Use
5. Surface Blocked Tasks
- If there are any Blocked tasks, list them with their
blockedReasonfrom devInfo:Blocked Tasks Requiring Human Attention: - [SLUG] Task title: <blockedReason> - 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
Signals
- GitHub stars
- 985
- Forks
- 276
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
orchestrate-hashgraph-online- Source
- github.com/hashgraph-online/awesome-codex-plugins