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-chat-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-chat-agents)<a href="https://agentmods.dev/skills/oaustegard/claude-skills/orchestrating-chat-agents"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/orchestrating-chat-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-chat-agents"><img src="https://agentmods.dev/badge/skills/oaustegard/claude-skills/orchestrating-chat-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 | $0.00104 | $0.04091 |
| Opus 5.5 | $0.00042 | $0.01636 |
| Sonnet 5.5 | $0.00021 | $0.00818 |
| Haiku 4.5 | $0.00010 | $0.00409 |
Grade A, and why
orchestrating-chat-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 5d 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 — 488 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.
Which native mechanism to use (Agent tool, Workflow, or headless claude -p
children launched from one background command) is dispatching-subagents.
In Claude Code the claude binary authenticates through the host, so a headless
fan-out needs no API key either.
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.
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 8.1 KB
- README.md 577 B
- references/api-reference.md 13 KB
- references/function-reference.md 7.5 KB
- references/workflows.md 10 KB
- scripts/agent_pool.py 14 KB runs code
- scripts/claude_client.py 47 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.
- 5d ago First seen · 488 lines · 104 tokens per session scan A 4e6671a1f8db
orchestrating-chat-agents is a skill published in the GitHub repository oaustegard/claude-skills (153 stars, last pushed yesterday), licensed MIT. It adds 104 tokens to every session and 4,091 once invoked, about $0.0004 per session on Opus 5.5. 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 2026-10-12.
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