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/commands/fitlab-ai/agent-infra/create-pr.zh-cn)<a href="https://agentmods.dev/commands/fitlab-ai/agent-infra/create-pr.zh-cn"><img src="https://agentmods.dev/badge/commands/fitlab-ai/agent-infra/create-pr.zh-cn/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/commands/fitlab-ai/agent-infra/create-pr.zh-cn"><img src="https://agentmods.dev/badge/commands/fitlab-ai/agent-infra/create-pr.zh-cn.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 | $0.00007 | $0.00066 |
| Opus 5.5 | $0.00003 | $0.00026 |
| Sonnet 5.5 | $0.00001 | $0.00013 |
| Haiku 4.5 | $0.00001 | $0.00007 |
Grade A, and why
create-pr.zh-CN 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.
What it actually says
读取并执行 .agents/skills/create-pr/SKILL.md 中的 create-pr 技能。
严格按照技能中定义的所有步骤执行。
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 · 9 lines · 7 tokens per session scan A b41f3ef8220d
create-pr.zh-CN is a command published in the GitHub repository fitlab-ai/agent-infra (86 stars, last pushed today), licensed MIT. It adds 7 tokens to every session and 66 once invoked, about $0.0000 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 2026-09-03.
Other commands, from other repositories
code-review
Review the current branch changes for bugs and style issues.
end
End a work session - a settlement pass that reconciles uncommitted / unpushed work + session context into git, the tracker, and a session snapshot file. --session (aliases --snapshot, --pre-compact, --compact) skips settlement and only writes the shared snapshot, keeping the session going.
pr-ready
Run the project's pre-commit review loop to determine whether the current branch is ready to push — lint, tests, parallel pr-review-toolkit agents plus an over-engineering audit, fix-and-re-run until convergence.
hatch3r-pr-resolve
Read open PR comments, evaluate each against current code via the rigor contract, implement accepted findings, reply inline. Multi-platform.
afrv
Revise the current feature worktree after code review — decide accept/revert/modify (shortcut for feature-code-revise).
create-pr
Create a pull request with proper template discovery and population.