Skippy Model Package
Mesh-LLM/mesh-llm
A skill your agent uses when inspecting GGUF models, planning layer ranges, generating or validating skippy package artifacts, fake packages for direct GGUFs, materialized stage cache behavior, or…
Package a G6-approved mathematical-modeling paper and its exact supporting code, data, results, and figures without changing their behavior or the workspace.
$ npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install zhnnky329/MathModeling-skills submission-packager --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ 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-srcUse ~/.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/
Install the "submission-packager" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.codex/skills/submission-packager into .claude/skills/submission-packager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "submission-packager", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/zhnnky329/MathModeling-skills/tree/main/.codex/skills/submission-packagerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install zhnnky329/MathModeling-skills submission-packager --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.codex/skills/submission-packager .agents/skills/submission-packager && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "submission-packager" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.codex/skills/submission-packager into .agents/skills/submission-packager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "submission-packager", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install zhnnky329/MathModeling-skills submission-packager --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.codex/skills/submission-packager .cursor/skills/submission-packager && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "submission-packager" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.codex/skills/submission-packager into .cursor/skills/submission-packager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "submission-packager", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/zhnnky329/MathModeling-skills.git --path .codex/skills/submission-packager--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install zhnnky329/MathModeling-skills submission-packager --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.codex/skills/submission-packager .gemini/skills/submission-packager && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "submission-packager" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.codex/skills/submission-packager into .gemini/skills/submission-packager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "submission-packager", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install zhnnky329/MathModeling-skills submission-packagerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/.codex/skills/submission-packager .github/skills/submission-packager && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "submission-packager" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.codex/skills/submission-packager into .github/skills/submission-packager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "submission-packager", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add zhnnky329/MathModeling-skills --skill submission-packager -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install zhnnky329/MathModeling-skills submission-packager --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/zhnnky329/MathModeling-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.codex/skills/submission-packager .opencode/skills/submission-packager && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "submission-packager" agent skill from https://github.com/zhnnky329/MathModeling-skills/tree/main/.codex/skills/submission-packager into .opencode/skills/submission-packager/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "submission-packager", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
submission-packagerPackage 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.
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.
5 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 0b46e9c. It shows what the files ask for, not the result of running them.
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.
Ships 1 file in scripts/ (Python), which the agent can run.
Shell commands in SKILL.md call:
pythonFrom the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
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.
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.
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.
The full file from zhnnky329/MathModeling-skills at commit 0b46e9c, republished under its MIT licence (© zhnnky329). 576 words, ~1,105 tokens.
.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.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.
planning/session_config.json selects rigor_profile: submission.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.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.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.
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.--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.--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.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.支撑材料/.支撑材料/ and their references in the packaged paper are updated. Unresolved image paths block packaging.© zhnnky329, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (scripts) in .codex/skills/submission-packager of zhnnky329/MathModeling-skills.
Open the folder on GitHubat commit 0b46e9c
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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Submission Packager this skillzhnnky329/MathModeling-skills | 1.1k | — | ~1.1k | Automated safety check: Pass | MIT | |
| Skippy Model PackageMesh-LLM/mesh-llm | 3.5k | — | ~588 | Automated safety check: Pass | Apache-2.0 | |
| OmniRoute Model Catalogdiegosouzapw/OmniRoute | 75k | — | ~589 | Automated safety check: Pass | MIT | |
| Model Bank Metadatalobehub/lobehub | 83k | — | ~2k | Automated safety check: Pass | Custom licence | |
| Harness Threat Modelruvnet/ruflo | 74k | — | ~363 | Automated safety check: Notes | MIT | |
| OmniRoute Model Catalog CLIdiegosouzapw/OmniRoute | 75k | — | ~554 | Automated safety check: Pass | MIT |
Mesh-LLM/mesh-llm
A skill your agent uses when inspecting GGUF models, planning layer ranges, generating or validating skippy package artifacts, fake packages for direct GGUFs, materialized stage cache behavior, or…
diegosouzapw/OmniRoute
Looks up which AI models an OmniRoute gateway can reach, creates or updates model aliases and tests whether individual models respond.
lobehub/lobehub
Fills and maintains the knowledgeCutoff, family and generation fields on model cards in LobeHub's model bank, from a single new model up to repo-wide backfills.
ruvnet/ruflo
Enterprise-review-grade threat model from harness threat-model {path}.
diegosouzapw/OmniRoute
Lists and manages AI models from the OmniRoute command line: browse a provider's catalog, search it, and add, edit, remove or test-add models.
openclaw/openclaw
Summarize CodexBar local cost logs by model for Codex or Claude, including current or full breakdowns.
zhnnky329/MathModeling-skills
Build and risk-screen a compact role-based method shortlist for a mathematical-modeling subquestion.
zhnnky329/MathModeling-skills
Classify each parsed mathematical-modeling subquestion by required output and structure, surface ambiguous framing trade-offs for human choice, and record primary/secondary task types without…
zhnnky329/MathModeling-skills
Map contest attachments to subquestions, audit and clean raw data, and emit one reusable data profile with quality, coverage, imbalance, concentration, and method-readiness evidence for downstream…
zhnnky329/MathModeling-skills
Build one compact choice card at a genuine mathematical-modeling judgment point.
zhnnky329/MathModeling-skills
Generate and run minimal reproducible MATLAB or Beita Tianyuan compatible code for the human-approved main method and usable baseline, with compact experiment artifacts and a canonical run summary.
zhnnky329/MathModeling-skills
Translate a human-approved main method and usable baseline into a minimal language-neutral implementation and experiment contract.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.