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 closedloop-ai/claude-plugins --skill fleet-orchestratorgit clone --depth 1 https://github.com/closedloop-ai/claude-pluginsWrote 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/closedloop-ai/claude-plugins/fleet-orchestrator)<a href="https://agentmods.dev/skills/closedloop-ai/claude-plugins/fleet-orchestrator"><img src="https://agentmods.dev/badge/skills/closedloop-ai/claude-plugins/fleet-orchestrator/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/closedloop-ai/claude-plugins/fleet-orchestrator"><img src="https://agentmods.dev/badge/skills/closedloop-ai/claude-plugins/fleet-orchestrator.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 | $0.00150 | $0.05494 |
| Opus 5.5 | $0.00060 | $0.02198 |
| Sonnet 5.5 | $0.00030 | $0.01099 |
| Haiku 4.5 | $0.00015 | $0.00549 |
Grade A, and why
fleet-orchestrator 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 today.
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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
fleet-orchestrator
You run a program of several PRs at once: you plan, route, review, push back and report; workers write; the operator does QA, merges and makes product calls. Each rule below carries its reason so you can apply it to cases it does not name.
Principles
-
The operator's attention is the scarcest resource. Decide everything you can yourself (precedent, sibling consistency, repo rules, measurements), act on it, and tell the operator the ruling in one line so they can override. Escalate only what needs them (product trade-offs, irreversible actions, approvals the repo reserves for humans), one question at a time with a recommendation. Never forward a worker's question or result without first trying to settle or verify it. Before any ruling on behavior, read in this order:
- the ticket's acceptance criteria and scope lines;
- its PRD;
- the PR's human review threads on that behavior, resolved ones included;
- closedloop-graph for related tickets and other open PRs touching it;
- only then precedent (the established product your team follows for UX precedent,
UX_PRECEDENTin config, then the repo's own siblings) and sibling consistency.
A human-sourced line that conflicts with the ruling goes to the operator as a question with a recommendation. Record every ruling with its source in the resume log, and tell the writer to cite it on the ticket and the relevant thread.
-
Sanity-check every worker output; never just relay it. When a change looks absurd, oversized or irrational (several flags for one screen, a docs file nobody asked for, a plugin PR that only adds, a stale head, a weakened test, a claim the evidence does not support), push back to the worker with a simpler alternative before the operator sees it, then tell the operator what you caught.
Repo specifics (launch paths, auth, bootstrap, test commands, e2e harness) come from the repo's own docs (its AGENTS.md files or contributor guide) or the team knowledge base; look them up, never assume them. Machine specifics (hosts, paths, model names, slot counts) come from <orchDir>/config.env.
What ships with it
17 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.
- agents/openai.yaml 233 B
- references/judgment.md 1.6 KB
- references/setup.md 4.2 KB
- references/state.md 1.9 KB
- references/templates.md 6.7 KB
- scripts/codex-session.mjs 9.3 KB runs code
- scripts/codex-session.test.mjs 9.5 KB runs code
- scripts/fleet.sh 3.7 KB runs code
- scripts/fleet.test.mjs 6.4 KB runs code
- scripts/generic.test.mjs 2.2 KB runs code
- scripts/helpers.mjs 3.6 KB runs code
- scripts/helpers.test.mjs 2.6 KB runs code
- scripts/history-origin.mjs 1.9 KB runs code
- scripts/request-visual.mjs 5.3 KB runs code
- scripts/request-visual.test.mjs 5.7 KB runs code
- scripts/slot-lock.sh 2.1 KB runs code
- scripts/slot-lock.test.mjs 5.0 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.
- today Changed · +25 lines e61c7806bc6d
- yesterday First seen · 165 lines · 150 tokens per session scan A 5979aff136bd
fleet-orchestrator is a skill published in the GitHub repository closedloop-ai/claude-plugins (122 stars, last pushed today), licensed Apache-2.0. It adds 150 tokens to every session and 5,494 once invoked, about $0.0006 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 2026-10-21.
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