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/854771076/oh-my-claude-rolesWrote 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/854771076/oh-my-claude-roles/audit-prompt-version)<a href="https://agentmods.dev/commands/854771076/oh-my-claude-roles/audit-prompt-version"><img src="https://agentmods.dev/badge/commands/854771076/oh-my-claude-roles/audit-prompt-version/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/854771076/oh-my-claude-roles/audit-prompt-version"><img src="https://agentmods.dev/badge/commands/854771076/oh-my-claude-roles/audit-prompt-version.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 | $0.00315 |
| Opus 5 | $0.00010 | $0.00158 |
| Sonnet 5 | $0.00004 | $0.00063 |
| Haiku 4.5 | $0.00002 | $0.00032 |
Grade A, and why
audit-prompt-version scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
命令内容
对指定范围的提示词版本变更进行合规性审核，确认是否符合企业版本管理规范。
变更范围：$ARGUMENTS
执行步骤：
- 使用Git获取指定范围的所有变更文件和提交信息
- 检查变更合规性：
- 版本号是否遵循语义化版本规范
- 提交信息是否符合Conventional Commits规范
- 是否附带了对应测试报告，测试是否全部通过
- 是否存在敏感信息硬编码、违规技术栈使用等问题
- 文件存储位置是否符合统一仓库、按模块分类规范
- 检查Code Review流程是否合规，是否有至少两名审批人
- 输出版本变更审核报告，给出是否可以合并上线的结论
检查要点：
- 必须检查所有变更文件，不能遗漏
- 必须确认敏感信息没有被提交到代码仓库
- 必须确认测试流程已经完成且全部通过
- 必须确认版本号升级符合语义化规范要求
- 不合规变更必须明确标注问题，给出调整建议
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 · 31 lines · 21 tokens per session scan A 0de1843d1e8d
audit-prompt-version is a command published in the GitHub repository 854771076/oh-my-claude-roles (22 stars, last pushed 5mo ago), licensed MIT. It adds 21 tokens to every session and 315 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 2026-08-30.
Other commands, from other repositories
prompt-audit
Discover and review LLM prompts in this codebase against the best-practices rubric. Reports findings and proposed diffs in the terminal — never edits without approval.
prompt
System instructions for writing effective prompts. Apply when generating commands, skills, agents, or any LLM instructions.
prompt-show
Display full details of a saved prompt by ID.
music-suno-prompt
Grounded Suno prompt synthesis from local knowledge corpus + persona canon + label canon. No vibes-prompting.
ai
Load the Kaizen skill for production-ready AI agent implementation with signature-based programming and multi-agent coordination.
audit-prompt
Evaluate an existing prompt for clarity, effectiveness, and edge cases.