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.
npx skills add chengziyue1222/math-model-agent --skill run-modeling-projectgit clone --depth 1 https://github.com/chengziyue1222/math-model-agentWrote 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/chengziyue1222/math-model-agent/run-modeling-project)<a href="https://agentmods.dev/skills/chengziyue1222/math-model-agent/run-modeling-project"><img src="https://agentmods.dev/badge/skills/chengziyue1222/math-model-agent/run-modeling-project/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/chengziyue1222/math-model-agent/run-modeling-project"><img src="https://agentmods.dev/badge/skills/chengziyue1222/math-model-agent/run-modeling-project.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 | $0.00048 | $0.00562 |
| Opus 5 | $0.00024 | $0.00281 |
| Sonnet 5 | $0.00010 | $0.00112 |
| Haiku 4.5 | $0.00005 | $0.00056 |
Grade A, and why
run-modeling-project 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 — 40 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run Modeling Project
Coordinate the existing Skills around a strong final paper. The project record supports reproducibility, but it is not a second product or a substitute for modeling.
Workflow
- Read
references/workflow-profiles.mdand chooserapid,competition(the default), orauditbefore creating deliverables. - Record the problem, data sources, deliverables and venue constraints. Apply CUMCM-only layout rules only when that venue requires them.
- Invoke
analyze-model-datawhere data is used andselect-modelfor decomposition, dependency analysis and structure opportunities. Invokeresearch-model-literaturewhen external facts, parameters, datasets, or citations affect a claim. - Invoke
solve-modelfor equations, algorithms, baselines, constraints, sensitivity and independent checks. - Invoke
make-model-figuresonly after identifying the conclusions each figure must establish. - Invoke
write-model-paperto turn verified results into a contest paper, thenreview-model-paperfor reader-visible and technical review. - Render and inspect the final PDF when the selected profile requires a paper; revise the original Skill outputs rather than creating a parallel demonstration workflow.
Priority Order
- final paper quality and layout;
- modeling and reasoning;
- validation and consistency;
- engineering convenience.
Read references/paper-first-flow.md for the actual handoff order. Existing manifests, stage gates and validations are permitted as backstage controls; their terms and traces do not belong in the submitted paper. In rapid, retain the non-negotiables but defer audit-only artifacts; do not label the result as formally verified.
Handoff Minimums
- analysis → selection: question decomposition, data/units, constraints and dependencies;
- selection → solution: model rationale, rejected alternatives, baseline and validation plan;
- solution → figures/writing: results, formulas, source tables, validations and limitations;
- figures → writing: claim, source, figure role, final artifact and interpretation;
- writing → review: manuscript, PDF, sources and a list of evidence used.
What ships with it
9 files 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.
- agents/openai.yaml 269 B
- references/handoff-schema.md 1.2 KB
- references/paper-first-flow.md 628 B
- references/production-rule-pack.md 958 B
- references/stage-gates.md 3.1 KB
- references/workflow-profiles.md 2.6 KB
- scripts/advance_project.py 3.5 KB runs code
- scripts/execute_skill.py 234 B runs code
- scripts/project_state.py 11 KB runs code
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 · 40 lines · 48 tokens per session scan A 7aac4f43981e
run-modeling-project is a skill published in the GitHub repository chengziyue1222/math-model-agent (16 stars, last pushed 29d ago), licensed MIT. It adds 48 tokens to every session and 562 once invoked, about $0.0002 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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