Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/agiflow/ai-plugin/orchestratenpx skills add AgiFlow/ai-plugin --skill orchestrategit clone --depth 1 https://github.com/AgiFlow/ai-pluginWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00064 | $0.01004 |
| Opus 5 | $0.00032 | $0.00502 |
| Sonnet 5 | $0.00013 | $0.00201 |
| Haiku 4.5 | $0.00006 | $0.00100 |
Grade A, and why
orchestrate scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to orchestrate — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 110 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 110 lines · 64 tokens per session scan A 2cc32b064197
orchestrate is a skill published in the GitHub repository AgiFlow/ai-plugin (2 stars, last pushed 1mo ago), licensed MIT. It adds 64 tokens to every session and 1,004 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to orchestrate, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
orchestrate
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 listtasks, listactivetasksbyorg, listmembers, updatetask, getworkunitprogress.
agency-os
Notion-as-source-of-truth dispatch board for running your work like an AI agency. One Tasks database is the source of truth; tasks flow Suggestion through Discussion, To-Do, In Progress, and Done with subtasks, recurring cadences, dependencies, and template subtrees. Batch execution fans approved To-Do rows out to…
goal-flight
Portable Goal Flight workflow for long-running repo work: planning, dispatch, review, recovery, file-backed resume.
dispatch
Use when a task file exists in .hyperflow/tasks/ and workers need dispatching. Fans out parallel workers under per-batch Reviewers, runs a final integration review, and commits per sub-task. Endpoint of the auto-chain — no auto-deploy. Trigger with /hyperflow:dispatch, "run the plan", "execute the task", "build it"…
roadmap
Maintain and update the Atmos roadmap page (website/src/data/roadmap.js): milestone/initiative/quarter schema, progress-percentage math, the curated featured[] cap (max 6, never auto-modified), and the no-changelog-for-internal-refactors gate. Invoke when adding/updating milestones, initiatives, or quarters, or…
handoff
Use when managing a two-session handoff — inspecting, picking up, or reviewing a committed handoff package produced by a session=two scope run. The operator interface over the cross-environment handoff lifecycle (plan in one session, build in another, review back in the first). Trigger with /hyperflow:handoff, "list…