mathmodel-skill AGENTS.md

Repository instructions for maintaining a mathematical modelling skill used for specific contest work, including CUMCM, MCM/ICM, and Diangong Cup competitions. They identify the authoritative workflow files, competition rules, templates, and packaging metadata.

In plain words
What is it for?
Use them when changing the mathmodel-skill repository, updating contest rules or stage guidance, maintaining decision-log templates, or checking plugin and skill packaging.
Why use it?
They prevent maintainers from applying the contest workflow to unrelated data analysis or paper review. They also help keep rules, persistent state, and documentation in the correct places.

Instructions file for CodexOpenCode

Install

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.

agentmods
npx agentmods add instructions/handsomezr-netizen/mathmodel-skill/agents-md
Clone the repo
git clone --depth 1 https://github.com/handsomeZR-netizen/mathmodel-skill

Made for: Codex, OpenCode.

Per session 604 This file is loaded in full into every session.
When invoked 604 The same file — it is already loaded in full.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00604 $0.00604
Opus 5 $0.00302 $0.00302
Sonnet 5 $0.00121 $0.00121
Haiku 4.5 $0.00060 $0.00060

Measured 3d ago against content hash a5e36c656642, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

mathmodel-skill AGENTS.md 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 3d 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.

AGENTS.md · 40 lines

How it starts

The opening of the file, as written. The whole thing — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Repository instructions

This repository contains the mathmodel-skill product. When working inside this repository, act as a maintainer: do not start the ten-stage contest workflow merely because modeling-related files are present.

Sources of truth

  • SKILL.md defines runtime behavior and trigger boundaries.
  • references/stage_00_kickoff.md through references/stage_09_review.md contain stage details and must be loaded lazily at runtime.
  • competitions/<competition>/ contains competition-specific rules, heuristics, overlays, and paper structures.
  • templates/shared/decision_log.json is the canonical persistent-state template.
  • .codex-plugin/plugin.json, agents/openai.yaml, and skills/mathmodel-skill/SKILL.md are packaging metadata or thin discovery shims. Do not duplicate the workflow into them.

Maintenance rules

  • Preserve the trigger boundary: this skill is for CUMCM, MCM/ICM, and Diangong Cup contest work, not generic data analysis or ordinary paper review.
  • Treat official contest rules as time-sensitive. Keep a verification date and primary source in competitions/<competition>/current_rules.md; official current-year material always overrides repository guidance.
  • Treat empirical distributions and winning_patterns.md as observations or maintainer heuristics, never official thresholds or award predictors.
  • Keep user artifacts relative to the user's working directory (state/, results/, figures/, paper_workspace/, paper_output/). Resolve repository resources relative to the installed skill root.
  • Keep SKILL.md concise and dispatch stage-specific detail into references/.
  • Do not add runtime claims about awards, token savings, or elapsed time without a reproducible benchmark.
  • When changing behavior, update the README, tests, plugin version, state schema, and relevant competition docs together.
  • Do not vendor or reintroduce templates, examples, papers, or binary assets without a clear redistribution license. Keep runtime dependencies and external-source boundaries accurate in THIRD_PARTY_NOTICES.md.

Read the full file on GitHub · 40 lines

Changes

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.

  1. 3d ago First seen · 40 lines · 604 tokens per session scan A a5e36c656642

Subscribe to this mod's changes

mathmodel-skill AGENTS.md is an instructions file published in the GitHub repository handsomeZR-netizen/mathmodel-skill (245 stars, last pushed 1mo ago), licensed MIT. It adds 604 tokens to every session, about $0.0030 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.

Related

Other instructions, from other repositories