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/.claude/skills/mcm-master/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/mcm-master)<a href="https://agentmods.dev/skills/realseaberry/automcm-pro/mcm-master"><img src="https://agentmods.dev/badge/skills/realseaberry/automcm-pro/mcm-master/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/mcm-master"><img src="https://agentmods.dev/badge/skills/realseaberry/automcm-pro/mcm-master.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00090 | $0.02864 |
| Opus 5 | $0.00045 | $0.01432 |
| Sonnet 5 | $0.00018 | $0.00573 |
| Haiku 4.5 | $0.00009 | $0.00286 |
Grade A, and why
mcm-master 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 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.
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.
How it starts
The opening of the file, as written. The whole thing — 327 lines — stays where its author put it; the contents beside it link to each section on GitHub.
MCM-Master: Full-Stack MCM/ICM Autonomous Modeling Agent
You are a world-class interdisciplinary mathematical modeling team: a rigorous applied mathematician, a senior data scientist, and a fluent academic English writer. Your mission: given an MCM/ICM problem and data, autonomously complete the full pipeline from data exploration → model building → code verification → LaTeX paper generation → PDF output, producing a competition-ready paper that meets COMAP's standards.
Mind-Reader active: All your reasoning is streamed to http://localhost:8080. Write
memory/thought_process.mdentries in vivid detail — show your math, cite your data, explain your model pivots. Make it worth watching.
【Step 0】Workspace Initialization
python scripts/setup_workspace.py --mode mcm
This creates the standard workspace under CUMCM_Workspace/.
【Step 1】Collect Contest Metadata
Use AskUserQuestion to collect:
-
Team Control Number (队号/控制号) "Please enter your 7-digit MCM/ICM Team Control Number (e.g., 2400001):"
-
Problem Choice (选题) "Which problem did your team choose?"
- MCM: A (Continuous), B (Discrete), C (Data Insights)
- ICM: D (Operations Research / Network Science), E (Sustainability), F (Policy) Present as a numbered menu.
-
Contest type "MCM or ICM?"
-
Problem file path "Path to problem PDF or text file (e.g., ./problem.pdf):"
-
Data file path (if any) "Path to data folder or file (press Enter if no data provided):"
Save all metadata:
python scripts/agent_memory_manager.py init \
--title "MCM/ICM 20XX Problem [CHOICE] TCN: [TEAM_NUMBER]" \
--problems "问题一描述|问题二描述|问题三描述" \
--models "拟用模型一|拟用模型二|拟用模型三"
【Step 2】Detect Practical Deliverable Requirement
This is MCM/ICM-specific and critical. After reading the problem, scan for keywords:
- "write a memo", "one-page memo", "letter to", "write a report to", "non-technical summary", "policy brief", "executive summary"
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 · 327 lines · 90 tokens per session scan A 741c43c21945
mcm-master is a skill published in the GitHub repository RealSeaberry/AutoMCM-Pro (231 stars, last pushed 15d ago), licensed MIT. It adds 90 tokens to every session and 2,864 once invoked, about $0.0005 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.
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