Getting it into your agent
This one installs as part of its plugin. Adding the marketplace and installing the plugin brings it with everything else the plugin ships.
/plugin marketplace add Abilityai/abilities/plugin install agent-devWrote 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/abilityai/abilities/agent-fleet-analysis)<a href="https://agentmods.dev/skills/abilityai/abilities/agent-fleet-analysis"><img src="https://agentmods.dev/badge/skills/abilityai/abilities/agent-fleet-analysis/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/abilityai/abilities/agent-fleet-analysis"><img src="https://agentmods.dev/badge/skills/abilityai/abilities/agent-fleet-analysis.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 | $0.00120 | $0.08674 |
| Opus 5.5 | $0.00048 | $0.03470 |
| Sonnet 5.5 | $0.00024 | $0.01735 |
| Haiku 4.5 | $0.00012 | $0.00867 |
Grade B, and why
agent-fleet-analysis scanned grade B with 1 finding 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 16d 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.
Reads MCP configurationmediumAgent snooping
mcp.json carries server URLs and auth tokens; reading it lets a mod discover and abuse other integrations.
If .gitignore exists, check it excludes: `.env`, `.env.*`, `.mcp.json`, `credentials.json`, `*.pem`, `*.key`, `content/`, `.claude/projects/`, and `.claude/plugins/`. Do **not** require `.claude/settings.json` — it is th How it starts
The opening of the file, as written. The whole thing — 514 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Fleet Analysis
ℹ️ First, set expectations: before anything else, print one short line with this skill's version and its most recent change — the top entry of
metadata.changelogabove — e.g.agent-fleet-analysis vX.Y — recent: <summary>. Then proceed.
Scan a collection of agents — Claude Code agents AND agents built any other way (n8n workflows, LangChain/CrewAI/AutoGen apps, freeform-coded LLM loops) — produce a strategic fleet design recommendation (hierarchy, knowledge brain, memory, canon layer) with every improvement mapped to an installable skill from the abilities plugin marketplace, and generate two artifacts:
- A4 PDF report — for humans, with a shareable download URL when running on Trinity.
- Markdown report — the machine-readable twin, written alongside the PDF. This is the agent-executable version: every gap, quick win, and roadmap item is a checkbox an agent can work through. Hand it to a Claude Code session (or the fleet hub) as the work order for fixing the fleet.
The report is useful regardless of deployment platform. It tells you how well your agents are designed, how they should be organized, and what's missing. If you want to run the fleet autonomously in the cloud, the last section shows how Trinity handles that — but the organizational work comes first and stands on its own.
Timescale framing (important): everything the report recommends is agent-executable work. A single Claude Code session can fix the gaps across every agent, create Trinity-compatible copies, and deploy them — in a couple of hours, not weeks. The roadmap phases are a sequence (do 1 before 2), never a calendar. Write the report accordingly: no "this week / next month" language anywhere.
Usage
/agent-fleet-analysis [path ...]
path(optional, one or more): directories to scan. Defaults to.(current directory). Multiple paths (space- or newline-separated) are scanned in one run and merged into a single report.
The skill is fully autonomous — it runs through all steps and prints the report locations (and a shareable URL when on Trinity) at the end.
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.
- 16d ago Changed · +1 lines 35319ed01647
- 1mo ago Changed · +1 lines f2e862b9c2d5
- 1mo ago First seen · 512 lines · 120 tokens per session scan B a518ec728e5c
agent-fleet-analysis is a skill published in the GitHub repository Abilityai/abilities (12 stars, last pushed 3d ago), licensed MIT. It adds 120 tokens to every session and 8,674 once invoked, about $0.0005 per session on Opus 5.5. A static security scan graded it B with 1 finding (reads mcp configuration). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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