Agent skill

Submission Packager

by zhnnky329 in zhnnky329/MathModeling-skills

Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.

MITAuto-check passed

Install Submission Packager

skills CLI
$ npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install zhnnky329/MathModeling-skills submission-packager --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.codex/skills/submission-packager .claude/skills/submission-packager && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
submission-packager
GitHub stars
1.1k
Token cost
~1.1k tokens
SKILL.md length
576 words
Files
2 (incl. scripts)
Skills in repo
29
Repo updated
First seen
Licence
MIT

At a glance

Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.

  • Works in 5 steps: Run python… → After the human confirms that exact… → The script copies selected source files… → …
  • Runs Python scripts from its folder; calls python

What it does

Submission Packager is an agent skill from zhnnky329/MathModeling-skills. Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including scripts (for example `scripts/package_submission.py`).

The repository describes itself as: 面向数学建模竞赛的 Claude Code / Codex Skills ,支持分阶段建模流程与 Python、MATLAB/北太天元代码分支。 The licence is MIT.

Example prompts

  • “/submission-packager”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Run python /scripts/package_submission.py --workspace with Python 3.9 or newer. This is a dry run and prints every copied source, its…
  2. After the human confirms that exact list, run the same command with --confirm . A changed source or plan blocks packaging. --out selects…
  3. The script copies selected source files into a staging directory, preserves their workspace-relative paths, rewrites only the packaged…
  4. When a safe reproduction command is available, pass --verify-command 'python code/Q1/run_all.py' (repeat per required command). Commands…
  5. Review the external manifest, package file hashes, runtime status, and actual Markdown image links. Only describe the package as runnable…

What it can do on your machine

Read from SKILL.md and the folder at commit 0b46e9c. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Submission Packager loads about 1.1k tokens when it runs. Until then it costs about 44 tokens; SKILL.md has 576 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~44
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from zhnnky329/MathModeling-skills at commit 0b46e9c, republished under its MIT licence (© zhnnky329). 576 words, ~1,105 tokens.

Download SKILL.mdSave it as .claude/skills/submission-packager/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
submission-packager
description
Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.

Purpose

Create one paper Markdown and one 支撑材料/ directory after the submission audits. Preserve selected code, inputs, and outputs under their workspace-relative paths. The packaged code must retain its module imports, CSV parsing, and normal working-directory paths. A packaging manifest stays outside the package at planning/submission_packaging_manifest.json.

Preconditions

  • planning/session_config.json selects rigor_profile: submission.
  • Every planning/manifests/Qx.json is at G6 and allows final assembly.
  • paper/audits/cross_media_consistency_audit.md, paper/audits/completeness_audit.md, and paper/qa_report.md each contain an explicit Verdict: PASSED line. Ask the relevant auditor to record the verdict when an older report omits it; do not infer passage from file existence.
  • The paper and freezes have not changed after those audits. Renew affected audits when they have.
  • Each Qx has a current frozen_numbers.json. Its source files identify one successful experiment round; that round's run_summary.json lists scripts, inputs, and outputs as workspace-relative paths. Update canonical run evidence through the normal workflow when a field is missing. Never select a round by its number alone.
  • A final paper/main.md exists, or supply another Markdown with --paper.

If the human explicitly authorizes packaging before G6, record their choice and rationale as a DECIDED human packaging_waiver in a decision ledger. Pass its decision_id with --allow-unaudited. The package manifest records this waiver and every failed gate or audit; never label it G6-approved.

Workflow

  1. Run python <skill-dir>/scripts/package_submission.py --workspace <ws> with Python 3.9 or newer. This is a dry run and prints every copied source, its destination, blocked items, and a SHA-256 plan digest. Check the actual contest's submission format and present the full inclusion list to the human.
  2. After the human confirms that exact list, run the same command with --confirm <plan digest>. A changed source or plan blocks packaging. --out selects another output directory. --force replaces only a previous, unchanged package recorded in the external manifest.
  3. The script copies selected source files into a staging directory, preserves their workspace-relative paths, rewrites only the packaged Markdown's image paths, checks Python syntax, then moves the verified stage into place. It rejects output paths containing the workspace or selected sources. The original workspace and the frozen sources stay untouched.
  4. When a safe reproduction command is available, pass --verify-command 'python code/Q1/run_all.py' (repeat per required command). Commands execute from the packaged 支撑材料/ directory after copied frozen outputs are removed, so they must recreate those outputs. Numerical JSON claims with a $.path locator are checked against frozen values using --atol and --rtol. Review command side effects before running. A missing command or unsupported locator is reported as UNVERIFIED, never as a runtime pass. MATLAB execution requires a compatible local runtime and an explicit command.
  5. Review the external manifest, package file hashes, runtime status, and actual Markdown image links. Only describe the package as runnable when the required reproduction checks passed.
Show full SKILL.md (122 more words)Show less

Selection and limits

  • Code comes from run_summary.json and its local Python/MATLAB dependencies. Inputs come from the summary and literal data paths in selected code. Outputs come from the summary and frozen sources. Paper images come from references in the delivered Markdown.
  • Preserve filenames and directories. Do not consolidate modules, prune comments, convert CSV files, rename data, or copy exploratory rounds, decision ledgers, audit files, or logs into 支撑材料/.
  • The paper is the only Markdown at the package root. Local paper images are copied beneath 支撑材料/ and their references in the packaged paper are updated. Unresolved image paths block packaging.
  • The manifest records evidence hashes, exact source-to-destination mapping, gate and audit evidence, selected frozen rounds, the confirmation digest, package hashes, and runtime status.

© zhnnky329, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (scripts) in .codex/skills/submission-packager of zhnnky329/MathModeling-skills.

  • SKILL.md
  • scripts/package_submission.py

Open the folder on GitHubat commit 0b46e9c

Compare with similar skills

Submission Packager next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Submission Packager compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Submission Packager this skillzhnnky329/MathModeling-skills1.1k—~1.1kAutomated safety check: PassMIT
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OmniRoute Model Catalogdiegosouzapw/OmniRoute75k—~589Automated safety check: PassMIT
Model Bank Metadatalobehub/lobehub83k—~2kAutomated safety check: PassCustom licence
Harness Threat Modelruvnet/ruflo74k—~363Automated safety check: NotesMIT
OmniRoute Model Catalog CLIdiegosouzapw/OmniRoute75k—~554Automated safety check: PassMIT

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Questions about Submission Packager

What does Submission Packager do?

Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace. Submission Packager is an agent skill from zhnnky329/MathModeling-skills. Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.

How do I install Submission Packager in Claude Code?

Run `npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a claude-code`. Or copy the skill folder (.codex/skills/submission-packager in zhnnky329/MathModeling-skills) into .claude/skills/submission-packager in your project. Claude Code loads it when a task matches its description.

How do I install Submission Packager in Codex?

Run `npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a codex`. Or copy the skill folder (.codex/skills/submission-packager in zhnnky329/MathModeling-skills) into .agents/skills/submission-packager in your project. Codex loads it when a task matches its description.

Can I use Submission Packager in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/submission-packager, .gemini/skills/submission-packager, .github/skills/submission-packager and .opencode/skills/submission-packager in your project.

What does Submission Packager need to run?

Going by SKILL.md and its folder, Submission Packager needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Submission Packager access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Submission Packager safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Submission Packager use?

Submission Packager is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Submission Packager use?

About 1.1k tokens (SKILL.md is roughly 4.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Submission Packager?

Skills that share tags, products or a category with Submission Packager: Skippy Model Package (Mesh-LLM/mesh-llm, 3.5k stars), OmniRoute Model Catalog (diegosouzapw/OmniRoute, 75k stars), Model Bank Metadata (lobehub/lobehub, 83k stars) and Harness Threat Model (ruvnet/ruflo, 74k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Submission Packager?

zhnnky329 (a GitHub user) maintains it in zhnnky329/MathModeling-skills, which has 1,060 GitHub stars. The repository holds 29 skills in this directory. The repository was last updated on September 24, 2026.

Source: zhnnky329/MathModeling-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.