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.
git clone --depth 1 https://github.com/fitlab-ai/agent-infraWrote 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/agents/fitlab-ai/agent-infra/agent-infra-lifecycle-executor.en)<a href="https://agentmods.dev/agents/fitlab-ai/agent-infra/agent-infra-lifecycle-executor.en"><img src="https://agentmods.dev/badge/agents/fitlab-ai/agent-infra/agent-infra-lifecycle-executor.en/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/agents/fitlab-ai/agent-infra/agent-infra-lifecycle-executor.en"><img src="https://agentmods.dev/badge/agents/fitlab-ai/agent-infra/agent-infra-lifecycle-executor.en.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 | $0.00070 |
| Opus 5 | $0.00010 | $0.00035 |
| Sonnet 5 | $0.00004 | $0.00014 |
| Haiku 4.5 | $0.00002 | $0.00007 |
Grade A, and why
agent-infra-lifecycle-executor 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.
What it actually says
Run only the requested non-review lifecycle skill for the supplied task reference. Do not run any review-* skill. Preserve the existing worktree, follow the selected skill completely, and stop after its completion output.
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 · 7 lines · 21 tokens per session scan A d9e1d523c1ab
agent-infra-lifecycle-executor is an agent published in the GitHub repository fitlab-ai/agent-infra (83 stars, last pushed today), licensed MIT. It adds 21 tokens to every session and 70 once invoked, about $0.0001 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 2026-09-03.
Other agents, from other repositories
atomic-auditor
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scout-external
Use when you need to locate files across a large codebase using external agentic tools (Gemini, OpenCode) for faster parallel searching with large context windows.
backend
Backend development expert for API design review, business logic analysis, error handling assessment, and performance evaluation. Use when reviewing server-side code, API endpoints, data processing, or service integrations.
ml-engineer
Use when you need to train models, optimize hyperparameters, implement training pipelines, deploy models to production, or debug model performance issues.