Borrowing it
Nothing to install: this file belongs to RealSeaberry/AutoMCM-Pro. 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/RealSeaberry/AutoMCM-Pro/main/.agents/skills/auto-mcm/SKILL.mdgit clone --depth 1 https://github.com/RealSeaberry/AutoMCM-ProWrote 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/realseaberry/automcm-pro/auto-mcm)<a href="https://agentmods.dev/skills/realseaberry/automcm-pro/auto-mcm"><img src="https://agentmods.dev/badge/skills/realseaberry/automcm-pro/auto-mcm/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/realseaberry/automcm-pro/auto-mcm"><img src="https://agentmods.dev/badge/skills/realseaberry/automcm-pro/auto-mcm.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Excessive Agency · line 87 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
- high Excessive Agency · line 87 Skill selects an external model or provider that may use a different account or billing plan than the operator expects. Undisclosed model switches can cause unexpected cost or quota consumption.Fix: Remove the model/provider override or disclose it prominently and require explicit operator approval before invoking an external coding CLI or billed model.
- medium Agent Snooping · line 16 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 17 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 36 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 90 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Agent Snooping · line 111 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
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 | $0.00084 | $0.02510 |
| Opus 5 | $0.00042 | $0.01255 |
| Sonnet 5 | $0.00017 | $0.00502 |
| Haiku 4.5 | $0.00008 | $0.00251 |
Grade A, and why
auto-mcm scanned grade A 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
| `Bash` | 顶层工具 `exec`（参数是一段 JS），内部调 `tools.exec_command({cmd,...})` | ✅ 实测确认（喚醒協議 Step 1 跑通）。万能工具：跑 Python 脚本、`cat` 读文件、`rg`/`grep`/`find` 搜索、`curl` 抓网页，本文件后续所有"执行 `python scripts/...`"都是这个模式，不是直接的扁平 function call | How it starts
The opening of the file, as written. The whole thing — 130 lines — stays where its author put it; the contents beside it link to each section on GitHub.
AutoMCM-Pro：Codex CLI 绑定
这是 AutoMCM-Pro 协议在 OpenAI Codex CLI 上的运行时绑定（Binding），不是另一套
独立协议。 行为规范权威来源仍是仓库根目录的 AutoMCM_SOP.md（工具无关，原样
复用）；可选探索层见 LOS_ALAMOS_DESIGN.md。Claude Code 绑定是
.claude/skills/auto-mcm/SKILL.md，DeepSeek Harness 绑定是
.dsh/skills/auto-mcm/SKILL.md——三份文件描述同一套流程，只是把"怎么调用工具"
换成各自 runtime 的实际工具，流程逻辑、Checkpoint 规则、质量门控、Prompt 内容
不应该在几份文件间产生分歧。完整背景见
CODEX_INTEGRATION.md。
【与其他 runtime 最大的差异：Codex 只给模型一个"代码模式"工具，实测确认】
这不是源码调研的推测，是实跑一次任务、解压
~/.codex/sessions/**/rollout-*.jsonl 核对过的：Codex 模型端 function-calling
只看得到一个叫 exec 的顶层工具，参数是一段 JavaScript 代码；
tools.exec_command({cmd, workdir, ...}) 是这段 JS 代码内部能调用的异步
函数，不是模型能单独调用的顶层工具。也就是说，Bash/Read（文本）在 Codex
上都是：模型写一段 JS，里面调用 tools.exec_command({cmd: "..."})，再用
text(r.output) 把结果吐出来——不是直接的 {"tool": "exec_command", "cmd": "..."} 这种扁平 function call。
实测时甚至连读 SKILL.md 本身也是这样做的：模型用
tools.exec_command({cmd: "sed -n '1,240p' .agents/skills/auto-mcm/SKILL.md"})
直接读档，没有专门的 skill 载入工具——这点跟 opencode/dsh 都不一样（它们有
独立的 skill 工具）。
这件事对 AutoMCM-Pro 反而是天然契合——本项目的流水线绝大部分工作本来就是
"用 bash 调 Python 脚本"，很少直接依赖结构化文件工具，翻译成 Codex 的
JS-in-exec 模式没有额外损失。
【工具映射表】
| Claude Code | Codex 工具 | 说明 |
|---|---|---|
Bash |
顶层工具 exec（参数是一段 JS），内部调 tools.exec_command({cmd,...}) |
✅ 实测确认（喚醒協議 Step 1 跑通）。万能工具：跑 Python 脚本、cat 读文件、rg/grep/find 搜索、curl 抓网页，本文件后续所有"执行 python scripts/..."都是这个模式，不是直接的扁平 function call |
Read |
同上，exec 里的 JS 调 tools.exec_command({cmd: "cat ..."}) |
✅ 实测确认（读 SKILL.md 本身就是这么做的） |
Read（图片） |
view_image |
专用图片查看工具，读图表/PDF 截图用它，不要用 cat |
Write/Edit |
apply_patch |
结构化 diff 应用工具，写/改模型代码、.tex 文件优先用它（比 shell heredoc 更可靠地保留缩进/编码） |
Glob/Grep |
exec_command 里 rg/find |
没有专用搜索工具 |
TodoWrite |
update_plan |
语义对应 |
AskUserQuestion |
请求用户输入的工具（模块 request_user_input，确切工具名未逐字核对，见下方核验清单） |
语义对应 |
Agent(description, prompt) |
多代理协同工具家族（模块 multi_agents/multi_agents_v2，确切工具名未逐字核对） |
Codex 有原生多代理能力，但这次没有把确切的工具调用 schema 读完，接入前务必先跑一个最小测试确认参数格式 |
WebSearch/WebFetch |
没有确认到的第一方工具 | 见下方【已知能力缺口】 |
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.
- 9d ago First seen · 130 lines · 84 tokens per session scan A ba87e5d33577
auto-mcm is a skill published in the GitHub repository RealSeaberry/AutoMCM-Pro (231 stars, last pushed 15d ago), licensed MIT. It adds 84 tokens to every session and 2,510 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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