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 skills add oaustegard/claude-skills --skill orchestrating-agentsgit clone --depth 1 https://github.com/oaustegard/claude-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/oaustegard/claude-skills/orchestrating-agents)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/orchestrating-agents"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/orchestrating-agents/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/oaustegard/claude-skills/orchestrating-agents"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/orchestrating-agents.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00082 | $0.04342 |
| Opus 5 | $0.00041 | $0.02171 |
| Sonnet 5 | $0.00016 | $0.00868 |
| Haiku 4.5 | $0.00008 | $0.00434 |
Grade A, and why
orchestrating-agents 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.
How it starts
The opening of the file, as written. The whole thing — 508 lines — stays where its author put it; the contents beside it link to each section on GitHub.
SURFACE ROUTING — read first
Fan-out has three possible engines. Which exist depends on where you are running. Pick the engine before writing any orchestration code.
| Engine | claude.ai | Cowork | Claude Code / CCotw |
|---|---|---|---|
Native subagents (Agent / Task / Workflow) |
✗ | ✓ | ✓ |
Gemini via CF AI Gateway (invoking-gemini) |
✓ | ✓ | ✓ |
| This skill's httpx fan-out (raw Anthropic API) | ✓ | last resort | last resort |
Primary discriminator — check the tool list, not the filesystem. If an Agent,
Task, or Workflow tool is callable, native subagents exist. That single fact
decides the row. Everything below is elaboration.
If native subagents exist (Cowork, Claude Code, CCotw)
Use them. Do not hand-roll from this skill. The managed runtime gives
16-concurrent / 1000-agent ceilings, an approval gate, adversarial cross-review,
and in-session resume — all of which this skill would reimplement worse. Route
model and effort per agent-routing (calibrated on 300 measured Haiku calls);
do not re-derive that here.
Cowork adds one option Claude Code doesn't: subagents can be declared rather
than spawned ad hoc, as agents/*.md in a plugin — frontmatter name,
description, model, effort, maxTurns, tools, disallowedTools,
skills, memory, background, isolation: worktree. They appear as
plugin-name:agent-name. Note hooks, mcpServers, and permissionMode are
refused in plugin agents for security, so a declared agent inherits the session's
MCP connections and cannot bring its own.
Reach back into this skill on those surfaces only for what the runtime lacks:
stall detection, or a long-lived ConversationThread. Inter-agent messaging is
NOT on that list — the runtime ships SendMessage and ListAgents, and
AgentPool reimplements them worse.
Native inter-agent messaging — SendMessage / ListAgents
ListAgents discovers reachable agents; SendMessage delivers plain text to one
by name or id. Both reach subagents, agent-team teammates, and independent
sessions. Official docs: code.claude.com/docs/en/cross-session-messaging
(shipped v2.1.224, macOS and Linux).
What ships with it
13 files 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.
- CHANGELOG.md 6.2 KB
- README.md 245 B
- references/api-reference.md 11 KB
- references/function-reference.md 7.4 KB
- references/workflows.md 10 KB
- scripts/agent_pool.py 14 KB runs code
- scripts/claude_client.py 44 KB runs code
- scripts/orchestration.py 18 KB runs code
- scripts/task_state.py 9.8 KB runs code
- scripts/test_caching.py 3.8 KB runs code
- scripts/test_integration.py 8.6 KB runs code
- scripts/test_interrupt.py 1.0 KB runs code
- scripts/test_streaming.py 1.4 KB runs code
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 Changed · -28 lines 1b6d77c97680
- 9d ago First seen · 536 lines · 82 tokens per session scan A 819db8fc5226
orchestrating-agents is a skill published in the GitHub repository oaustegard/claude-skills (148 stars, last pushed yesterday), licensed MIT. It adds 82 tokens to every session and 4,342 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
superdesign
Design or redesign frontend UI, presentations, and graphics on the Superdesign canvas with a choice of leading AI models. Use whenever the user wants to design a page, feature, flow, slide deck, or brand-new product; improve or reproduce existing UI; compare design results across top models; explore visual variants…
Linear
Managing Linear issues, projects, and teams. Use when working with Linear tasks, creating issues, updating status, querying projects, or managing team workflows.
chanlun-engine-skill
A Chinese-language stock-analysis skill based on Chan theory, a method for interpreting price-chart structures such as turning points and trading ranges.
youtube-summary
Summarize a YouTube video into structured notes — TL;DR, key takeaways, chapter-by-chapter breakdown, and reference links. Use when the user shares a YouTube URL (or invokes /youtube-summary ) and wants a summary, takeaways, transcript notes, or a write-up of a talk, lecture, or tutorial. Fetches the transcript and…
plangate
Use for any non-trivial task with 2+ open decisions/tradeoffs OR multiple implementation steps — instead of deliberating one question at a time in chat, write a structured plan to a file and let the user review it inline in vim with > Q: / > A: blockquote markers, then revise until agreed before touching any code.…
coinmarketcap
Expert assistant for CoinMarketCap Pro API — price quotes, listings, historical OHLCV, market metrics, Fear & Greed Index, CMC100/CMC20 indices, exchange data, DEX data, airdrops, trending, community sentiment. Covers 10+ endpoint categories across REST + MCP + x402 pay-per-call modes. Use when the user wants: current…