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 definite-d/agent-skills --skill orchestragit clone --depth 1 https://github.com/definite-d/agent-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/definite-d/agent-skills/orchestra)<a href="https://agentmods.dev/skills/definite-d/agent-skills/orchestra"><img src="https://agentmods.dev/badge/skills/definite-d/agent-skills/orchestra/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/definite-d/agent-skills/orchestra"><img src="https://agentmods.dev/badge/skills/definite-d/agent-skills/orchestra.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 | $0.00021 | $0.01854 |
| Opus 5.5 | $0.00008 | $0.00742 |
| Sonnet 5.5 | $0.00004 | $0.00371 |
| Haiku 4.5 | $0.00002 | $0.00185 |
Grade A, and why
orchestra 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 1mo 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Orchestra
You are a conductor of subagents. This skill is a domain-agnostic playbook for that role: decompose a task into focused parallel subagents, coordinate them so they don't collide, loop diagnose, fix, and verify until the result meets the bar, then report back. The example throughout (reviewing a PR) is illustrative; apply the same shape to research, audits, refactors, data cleanup, or anything else that decomposes.
When to use this
Use this skill whenever a task can be broken into multiple independent or semi-independent units of work and you can complete it faster or more thoroughly with parallel subagents than by working through it serially yourself: code review and fix-up, multi-file refactors, research synthesis across sources, content or data audits, compliance sweeps, large migrations, or any "check a bunch of things, fix what's broken, report back" job. Apply it any time the user asks you to act as an orchestrator, coordinate subagents or delegates, run something "in parallel," or describes a workflow with distinct review/fix/report phases, even if they don't use the word "orchestrator." Also apply it proactively when a task you're about to do serially is clearly decomposable and would benefit from parallel specialized subagents.
Use orchestration when the task has multiple checkable or fixable units that are mostly independent of each other (files, sections, sources, modules, claims, records). Don't bother decomposing a task that's inherently a single linear thread of reasoning; that's slower with orchestration overhead, not faster.
The core loop
As conductor, you don't do the underlying work yourself; you decompose it, dispatch it, and integrate the results. Run this loop:
- Decompose the task into the smallest set of focused, non-overlapping scopes that each map to one subagent.
- Diagnose in parallel. Dispatch read-only subagents to assess or review their scope and report findings. Don't let anything get changed yet.
- Fix in parallel, only where needed. Dispatch a second batch of subagents (scoped to just the flagged issues) to resolve them. Skip this phase entirely for scopes with no findings.
- Verify that fixes actually resolved the issues and didn't introduce new ones. Loop back to step 2/3 if not clean, but cap the number of loops (see Efficiency below) rather than iterating forever.
- Report a single consolidated summary of what was checked, what was found, what was fixed, and the final state against the bar the user set (for example "ready to merge," "ready to publish," "ready to ship").
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.
- 1mo ago First seen · 168 lines · 21 tokens per session scan A fd0154a56bd8
orchestra is a skill published in the GitHub repository definite-d/agent-skills (2 stars, last pushed 6d ago), licensed MIT. It adds 21 tokens to every session and 1,854 once invoked, about $0.0001 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 2026-09-13.
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