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 seb1n/awesome-ai-agent-skills --skill multi-agent-orchestrationgit clone --depth 1 https://github.com/seb1n/awesome-ai-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/seb1n/awesome-ai-agent-skills/multi-agent-orchestration)<a href="https://agentmods.dev/skills/seb1n/awesome-ai-agent-skills/multi-agent-orchestration"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/multi-agent-orchestration/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/seb1n/awesome-ai-agent-skills/multi-agent-orchestration"><img src="https://agentmods.dev/badge/skills/seb1n/awesome-ai-agent-skills/multi-agent-orchestration.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00071 | $0.01089 |
| Opus 5 | $0.00036 | $0.00544 |
| Sonnet 5 | $0.00014 | $0.00218 |
| Haiku 4.5 | $0.00007 | $0.00109 |
Grade A, and why
multi-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 11d 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 — 75 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Multi-Agent Orchestration
Use multiple agents only when specialization or safe parallelism outweighs coordination cost.
Use when
- Split a large objective into independent, verifiable workstreams.
- Coordinate specialists that need distinct tools, permissions, or context.
- Run worker-reviewer, planner-executor, map-reduce, or bounded debate patterns.
- Diagnose duplicate work, conflicting edits, weak handoffs, or stalled dependencies.
Do not delegate a tightly coupled, small, or inherently sequential task merely to increase agent count.
Inputs
Collect the objective, completion criteria, task graph, available agents and tools, concurrency limits, shared files or systems, authority boundaries, deadlines, budget, and final decision owner. State assumptions and unresolved dependencies.
Output contract
Produce:
- A decomposition rationale and explicit non-goals.
- A directed acyclic task graph with owner, dependencies, inputs, output contract, write scope, and verification for every task.
- A handoff protocol and shared-state policy.
- Approval points, timeout and retry limits, escalation routes, and stop conditions.
- A synthesis plan that resolves disagreements and verifies the integrated result.
- A completion report with evidence, remaining uncertainty, and unused or failed branches.
Workflow
- Define one measurable objective and the authority boundary before assigning work.
- Decompose by separable outputs, not vague roles. Keep shared mutable state to a minimum and retain tightly coupled steps under one owner.
- Draw dependencies and identify the critical path. Parallelize only tasks with independent inputs and non-overlapping side effects. Read orchestration-patterns.md when choosing a topology.
- Assign one accountable owner per task. Specify inputs, deliverable format, write scope, validation, deadline or timeout, and what warrants escalation.
- Give each agent the minimum context and permissions needed. Include source artifacts, not hidden conclusions, when independent judgment matters.
- Require structured handoffs: status, result, evidence, changed state, assumptions, risks, and next dependency. Acknowledge receipt before downstream mutation.
- Monitor dependency state and useful progress. Bound retries and debates; do not recursively delegate without a clear capacity and ownership model.
- Synthesize centrally or through a named integrator. Resolve conflicting claims from primary evidence, run integration checks, and confirm the original completion criteria.
- Close or cancel unused work, record unresolved risks, and return control to the final decision owner.
What ships with it
3 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.
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.
- 11d ago First seen · 75 lines · 71 tokens per session scan A 6a7f61e5adb5
multi-agent-orchestration is a skill published in the GitHub repository seb1n/awesome-ai-agent-skills (179 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 1,089 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 2026-08-30.
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