Borrowing it
Nothing to install: this file belongs to huangzhonglv/hep-workflow. 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/huangzhonglv/hep-workflow/main/.agents/skills/hep-paper-formalize/SKILL.mdgit clone --depth 1 https://github.com/huangzhonglv/hep-workflowWrote 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/huangzhonglv/hep-workflow/hep-paper-formalize)<a href="https://agentmods.dev/skills/huangzhonglv/hep-workflow/hep-paper-formalize"><img src="https://agentmods.dev/badge/skills/huangzhonglv/hep-workflow/hep-paper-formalize/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/huangzhonglv/hep-workflow/hep-paper-formalize"><img src="https://agentmods.dev/badge/skills/huangzhonglv/hep-workflow/hep-paper-formalize.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 | $0.00142 | $0.04859 |
| Opus 5 | $0.00071 | $0.02429 |
| Sonnet 5 | $0.00028 | $0.00972 |
| Haiku 4.5 | $0.00014 | $0.00486 |
Grade A, and why
hep-paper-formalize 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 11d 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 — 374 lines — stays where its author put it; the contents beside it link to each section on GitHub.
HEP Paper Formalizer
Turn a published paper into the workspace artifacts needed for paper-anchored
reproduction. This skill has two independent modes: Setup mode authors the
literature/ inputs, and Formalize mode reads literature/paper-extract.json
to author model/, constraints/, and model/benchmarks.json. Both modes write
only private foundation candidates and require mechanical finalization before
their outputs become authoritative.
This skill operates under docs/contracts/honest-reproduction-principle.md.
Paper formulas, curves, tables, and benchmark numbers are comparison targets
only. They must not become computational backends for Package-X, Python
translation, scans, or reproduction verdicts.
Mode selection is normally made by repro-orchestrator from
manifest.artifacts.model.status: a paper-first project runs Setup then
Formalize; a project that already has a model can run Setup only; a project
with existing literature/paper-extract.json can run Formalize only.
1. Mode Classification
Classify the mode before reading or writing artifacts.
| Mode | Inputs | Use when | First action | Hard fails |
|---|---|---|---|---|
setup-only |
Paper identifier or PDF path; project name or existing project directory | Add literature/ artifacts to a project whose model already exists, or prepare comparison targets before later formalization |
Locate or initialize the skeleton, allocate a Setup candidate, then author the literature files | Missing paper identifier; request to write calculation outputs; no user decision on target subset when target selection is ambiguous |
formalize-only |
Existing literature/paper-extract.json; project directory |
Convert a completed paper extract into model/, constraints/, and benchmark artifacts |
Allocate a Formalize candidate, then read its seeded extract and author model/constraint files | Missing paper extract; extracted formulas requested as calculation backend; request to fetch latest external constraints instead of using the paper |
setup+formalize |
Paper identifier or PDF path; project name or empty project directory | Build a paper-first workspace from scratch | Run Setup mode through user target confirmation, then continue into Formalize mode | Any Setup hard fail; user declines target set; unresolved canonical naming conflicts |
What ships with it
8 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.
- references/paper-extract-contract.md 5.1 KB
- references/paper-meta-contract.md 1.9 KB
- references/repro-targets-contract.md 13 KB
- scripts/init_paper_project_skeleton.py 3.5 KB runs code
- templates/paper-extract.example.json 5.7 KB
- templates/paper-meta.example.json 429 B
- templates/paper-style.mplstyle 1.0 KB
- templates/repro-targets.example.json 13 KB
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.
- 11d ago First seen · 374 lines · 142 tokens per session scan A 80eca5f67784
hep-paper-formalize is a skill published in the GitHub repository huangzhonglv/hep-workflow (9 stars, last pushed 1mo ago), licensed MIT. It adds 142 tokens to every session and 4,859 once invoked, about $0.0007 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 2026-08-31.
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