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/codeaholicguy/ai-devkit/agent-orchestrationnpx skills add codeaholicguy/ai-devkit --skill agent-orchestrationgit clone --depth 1 https://github.com/codeaholicguy/ai-devkitWhat 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 | $0.00057 | $0.00388 |
| Opus 5 | $0.00028 | $0.00194 |
| Sonnet 5 | $0.00011 | $0.00078 |
| Haiku 4.5 | $0.00006 | $0.00039 |
Grade A, and why
agent-orchestration 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 yesterday.
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.
What it actually says
Agent Orchestration
Use only for multi-agent supervision: coordinating dependencies, polling progress, unblocking waiting agents, relaying outputs, resolving conflicts, and verifying completion across agents. For one-off list/detail/send/start/kill work, use $agent-management or $agent-communication.
Use $agent-management for safe agent selection and lifecycle actions. Use $agent-communication for list/detail/send mechanics. Use $verify before accepting any agent's completion claim.
Rules
- Own the loop until assigned work is complete, blocked, or stopped.
- Run
agent list --jsonbefore each pass; never assume names/statuses. - Inspect waiting, idle, unknown, missing, or stale agents before acting.
- Send self-contained instructions and avoid duplicate follow-ups.
- Sequence agents that touch the same files; relay only relevant upstream output.
- Escalate only for repeated failures, unresolved conflicts, product/business decisions, or destructive/shared/production/security-sensitive actions.
Loop
If the goal or agent ownership is unclear, run one scan/detail pass. Ask the user once only if context is still insufficient.
- Scan agents.
- Assess agents needing attention with
detail --tail 10. - Act: approve, clarify, correct, delegate, relay, verify, or escalate.
- Report one brief status line.
- Sleep 10-60s and repeat.
Completion
Finish when all assigned work is verified, blocked with a clear reason, or stopped by the user. Summarize per-agent outcomes, verification, unresolved issues, and next step.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday First seen · 34 lines · 57 tokens per session scan A e5f5d0b9d97d
agent-orchestration is a skill published in the GitHub repository codeaholicguy/ai-devkit (1,601 stars, last pushed 2d ago), licensed MIT. It adds 57 tokens to every session and 388 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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