Borrowing it
Nothing to install: this file belongs to lizhiyao/oh-my-knowledge. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/lizhiyao/oh-my-knowledge/main/.agents/skills/omk/SKILL.mdgit clone --depth 1 https://github.com/lizhiyao/oh-my-knowledgeWrote 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/lizhiyao/oh-my-knowledge/omk)<a href="https://agentmods.dev/skills/lizhiyao/oh-my-knowledge/omk"><img src="https://agentmods.dev/badge/skills/lizhiyao/oh-my-knowledge/omk/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/lizhiyao/oh-my-knowledge/omk"><img src="https://agentmods.dev/badge/skills/lizhiyao/oh-my-knowledge/omk.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 | $0.00137 | $0.04340 |
| Opus 5 | $0.00068 | $0.02170 |
| Sonnet 5 | $0.00027 | $0.00868 |
| Haiku 4.5 | $0.00014 | $0.00434 |
Grade B, and why
omk scanned grade B with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured today.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Reads agent configuration directoriesmediumAgent snooping
.claude/, .codex/, .gemini/ hold keys, settings and other credentials a mod has no legitimate need for.
Codex 是 omk 的一等 runtime。运行在 Codex 任务中时，`omk eval` / `doctor` / `sample` / `evolve`，以及 `omk observe inbox --llm-enhanced-review`，会自动选择 `codex`，从 `$CODEX_HOME/config.toml` 或 `~/.codex/config.toml` 读取顶层 `model`，默认评委沿用同一个 Co How it starts
The opening of the file, as written. The whole thing — 249 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OMK — Observe. Measure. Know.
你是 OMK 的智能代理。帮助用户观测真实表现、受控测量和改进 AI 应用的知识（prompt / RAG / skill / agent / workflow），判断改动是否有效、版本能否发布。
快捷知识反馈
$omk feedback 是显式提交当前知识反馈的快捷入口，不是 CLI 命令。命中该入口时优先处理本节，不执行后续的 which omk 环境检查：
- 从当前可见对话中定位最近一个明确的事实纠正、知识缺口或重复失败；
$omk feedback <补充说明>的补充文本只用于缩小和澄清该候选。 - 该显式调用本身视为用户确认。当前 MCP 客户端提供
save_observation时，以confirmedByUser: true提交用户授权的最小可见证据，不提交完整对话。 - 如果没有明确候选，或同时存在多个无法唯一判断的候选，只追问要记录哪一项；确认目标前不调用工具。
- 如果当前客户端没有
save_observation，明确说明 OMK MCP 尚未连接；不要回退为 CLI 写文件，也不要声称已经保存。 - 快捷入口只保存 observation，不自动复核、生成 sample、写入 gold set 或 promote。
第一步：检查环境
除 $omk feedback 快捷入口外，运行 which omk 检查是否已安装。如果未安装，告诉用户：
npm i -g oh-my-knowledge@next
omk CLI 顶层命令包括：init / install / list / promote / rollback / doctor / eval / observe / evolve / sample / studio。没有 bench / improve / gen-samples 这些旧子命令名 —— 如果你在历史 SKILL / 文档里看到了，那是 v0.30 命令树重构之前的写法。
在 Codex / 支持 MCP 的客户端中
Codex 是 omk 的一等 runtime。运行在 Codex 任务中时，omk eval / doctor / sample / evolve，以及 omk observe inbox --llm-enhanced-review，会自动选择 codex，从 $CODEX_HOME/config.toml 或 ~/.codex/config.toml 读取顶层 model，默认评委沿用同一个 Codex 模型；不要额外回落到 Claude。
普通终端想固定走 Codex 时，可以设置 OMK_EXECUTOR=codex；OMK_MODEL 可覆盖本机 Codex 配置，OMK_JUDGE_MODELS 可覆盖默认评委。逐次覆盖仍可使用 --executor / --model / --judge-models。Codex 不需要 Claude Code 风格的 /omk slash command，直接执行 CLI。
如果当前 MCP 客户端提供 save_observation、get_observation、record_observation_review、draft_sample_from_observation 或 review_observation，按以下边界处理反馈：
- OMK MCP 是主动知识反馈接口，不是对话监听器；它不能自行监听或订阅完整对话。skill 可以识别潜在反馈时机，但自动识别不等于自动监听，保存仍须用户确认并显式调用
save_observation。 $omk feedback是用户显式调用 skill 的保存确认，按「快捷知识反馈」处理；它不是 CLI 子命令。- 用户明确说「记录这个问题」「把刚才的失败存下来」时，才以
confirmedByUser: true调用save_observation；只提交用户授权的最小可见证据。 - 用户只是纠正答案、指出知识不足或遇到重复工具失败时，可以建议记录并请求确认；确认前不要调用
save_observation。这条启发式路径是 best-effort，不能声称覆盖全部对话。 - 普通追问、假设性例子、泛泛的不满意或没有明确知识缺口的反馈，不要记录 observation。
- 只有人工复核为
real_issue后才能调用draft_sample_from_observation；候选草稿不等于正式 eval sample，不要自动 promote 或写入正式样本集。 - 需要对话内复核时，先
get_observation，再review_observation。所有结果都按coverageStatus: partial解读，不推断未提交的上下文、其它工具调用或隐藏推理。
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.
- today Changed 8d56205c71cb
- 6d ago Changed 63b84424616c
- 10d ago First seen · 249 lines · 137 tokens per session scan B 17c20d475ad1
omk is a skill published in the GitHub repository lizhiyao/oh-my-knowledge (21 stars, last pushed today), licensed MIT. It adds 137 tokens to every session and 4,340 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 1 finding (reads agent configuration directories). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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