LLM Benchmarking with lm-evaluation-harness
Orchestra-Research/AI-Research-SKILLs
Runs lm-evaluation-harness to benchmark language models on academic suites such as MMLU, GSM8K and HumanEval, compare models and track training checkpoints.
Document a deployed ML/AI model so others can use it responsibly.
Install Model Card
$ npx skills add mohitagw15856/pm-claude-skills --skill model-card -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install mohitagw15856/pm-claude-skills model-card --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/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/model-card .claude/skills/model-card && 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 "model-card" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/model-card into .claude/skills/model-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "model-card", 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/mohitagw15856/pm-claude-skills/tree/main/skills/model-cardType 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 mohitagw15856/pm-claude-skills --skill model-card -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install mohitagw15856/pm-claude-skills model-card --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/model-card .agents/skills/model-card && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "model-card" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/model-card into .agents/skills/model-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "model-card", 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 mohitagw15856/pm-claude-skills --skill model-card -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install mohitagw15856/pm-claude-skills model-card --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/model-card .cursor/skills/model-card && 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 "model-card" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/model-card into .cursor/skills/model-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "model-card", 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/mohitagw15856/pm-claude-skills.git --path skills/model-card--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 mohitagw15856/pm-claude-skills --skill model-card -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install mohitagw15856/pm-claude-skills model-card --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/model-card .gemini/skills/model-card && 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 "model-card" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/model-card into .gemini/skills/model-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "model-card", 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 mohitagw15856/pm-claude-skills model-cardInstalls 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 mohitagw15856/pm-claude-skills --skill model-card -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/model-card .github/skills/model-card && 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 "model-card" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/model-card into .github/skills/model-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "model-card", 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 mohitagw15856/pm-claude-skills --skill model-card -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install mohitagw15856/pm-claude-skills model-card --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/mohitagw15856/pm-claude-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/model-card .opencode/skills/model-card && 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 "model-card" agent skill from https://github.com/mohitagw15856/pm-claude-skills/tree/main/skills/model-card into .opencode/skills/model-card/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "model-card", 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.
Facts
- Skill name
model-card- GitHub stars
- 1.4k
- Token cost
- ~1k tokens
- SKILL.md length
- 503 words
- Files
- 1
- Skills in repo
- 1,348
- Repo updated
- First seen
- Licence
- MIT
At a glance
Document a deployed ML/AI model so others can use it responsibly.
- Asked to write a model card
- SKILL.md covers Required Inputs, Output Format, Quality Checks and Anti-Patterns, plus 2 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Document a models intended use and limitations
What it does
Model Card is an agent skill from mohitagw15856/pm-claude-skills. Document a deployed ML/AI model so others can use it responsibly. Use when asked to write a model card, document a model's intended use and limitations, or prepare an AI model for review/launch. Produces a complete model card — intended use, training data, evaluation metrics across slices, limitations, ethical considerations, and a deployment checklist.
Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in AI & LLM Engineering, covering Model hubs and datasets. The repository describes itself as: 1255 professional Agent Skills for Claude, ChatGPT, Gemini, Cursor & Codex — PRDs, postmortems, leases, medical bills, layoffs, go-bags, new countries. Plain markdown, MIT, in… The licence is MIT.
When your agent uses it
- Asked to write a model card
- Document a models intended use and limitations
- Prepare an AI model for review/launch
Example prompts
- “/model-card”
What it can do on your machine
Read from SKILL.md and the folder at commit 1cbf1f0. 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
No scripts in the folder and no shell commands in SKILL.md.
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
Model Card loads about 1k tokens when it runs. Until then it costs about 92 tokens; SKILL.md has 503 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.
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); files beside SKILL.md are not scanned.
SKILL.md
The full file from mohitagw15856/pm-claude-skills at commit 1cbf1f0, republished under its MIT licence (© mohitagw15856). 503 words, ~1,007 tokens.
Download SKILL.mdSave it as
.claude/skills/model-card/SKILL.md (or your agent's skills folder).- name
- model-card
- description
- Document a deployed ML/AI model so others can use it responsibly. Use when asked to write a model card, document a model's intended use and limitations, or prepare an AI model for review/launch. Produces a complete model card — intended use, training data, evaluation metrics across slices, limitations, ethical considerations, and a deployment checklist.
Model Card Skill
A model card is the README for a model: what it does, what it was trained and evaluated on, where it works, and — most importantly — where it doesn't. It turns an opaque artifact into something a reviewer, a downstream team, or a regulator can actually assess. Write it before launch, not after.
Required Inputs
Ask for these only if they aren't already provided:
- Model name & version, owner team, and date.
- What it does — task type (classification, generation, ranking, extraction…) and the decision it informs.
- Intended use & users — the supported use cases, and explicitly the out-of-scope ones.
- Training data — sources, size, time range, and known gaps (link a
dataset-datasheetif one exists). - Evaluation — datasets, metrics, and results, ideally broken down by subgroup/slice.
- Known limitations & risks — failure modes, bias findings, safety concerns.
Output Format
Model Card: [name] v[version]
Owner: [team] · Date: [date] · Status: [in review / production / deprecated]
1. Overview — one paragraph: what the model does, the decision it serves, and who uses it.
2. Intended Use
- In scope: the use cases this model is validated for.
- Out of scope / do not use for: explicit prohibited or unvalidated uses (this section prevents the most harm).
- Users: who is expected to operate or consume it.
3. Training Data — sources, size, time window, labelling method, and known coverage gaps.
4. Evaluation
- Metrics: the primary metric(s) and why they were chosen for this task.
- Overall results: headline numbers vs. a stated baseline.
- Sliced results: a table of the key metric across important subgroups (geography, language, device, demographic where appropriate) — surface where performance drops, don't hide it behind an average.
| Slice | N | Metric | vs. overall |
|---|
5. Limitations & Failure Modes — concrete situations where it underperforms or should not be trusted.
6. Ethical Considerations & Bias — fairness findings, sensitive-attribute handling, and mitigations applied.
7. Deployment & Monitoring — serving constraints (latency/cost), the drift/quality signals you'll watch, and the rollback trigger.
Show full SKILL.md (192 more words)Show less
Quality Checks
- "Out of scope / do not use for" is filled in with specifics — not left blank
- Evaluation is reported by slice, not just one global average that hides subgroup harm
- Every metric states the baseline it's measured against
- Limitations describe real, concrete failure situations (not "the model may be imperfect")
- A monitoring signal and an explicit rollback trigger are named
Anti-Patterns
- Do not report a single aggregate metric and call evaluation done — averages mask the slices where a model fails worst
- Do not leave "intended use" open-ended — an undefined boundary is an invitation to misuse
- Do not omit known biases because they're uncomfortable — an undocumented risk is a worse liability than a documented one
- Do not present accuracy without the class balance / base rate — 95% accuracy on a 95/5 split is meaningless
- Do not ship without a monitoring plan — a model card without a rollback trigger is a snapshot, not a contract
Based On
Model Cards for Model Reporting (Mitchell et al., 2019) and the model-documentation practice used in responsible-AI reviews.
Example Trigger Phrases
- "Write a model card."
- "Document a model's intended use and limitations."
- "Prepare an AI model for review/launch."
© mohitagw15856, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in skills/model-card of mohitagw15856/pm-claude-skills.
Open the folder on GitHubat commit 1cbf1f0
Compare with similar skills
Model Card 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 |
|---|---|---|---|---|---|---|
| Model Card this skillmohitagw15856/pm-claude-skills | 1.4k | — | ~1k | Automated safety check: Pass | MIT | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| SageMaker Serving Image Selectionhuggingface/skills | 11k | 1 repos | ~4.6k | Automated safety check: Pass | Apache-2.0 | |
| Hugging Face Local Model Evalshuggingface/skills | 11k | 2 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Upload Post Imagehuggingface/blog | 3.5k | — | ~1.1k | Automated safety check: Pass | None | |
| Esmfold2JimLiu/science-skills | 228 | 4 repos | ~2.5k | Automated safety check: Pass | Apache-2.0 |
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Related
Categories
Questions about Model Card
What does Model Card do?
Document a deployed ML/AI model so others can use it responsibly. Model Card is an agent skill from mohitagw15856/pm-claude-skills. Document a deployed ML/AI model so others can use it responsibly.
When should I use Model Card?
Model Card fits situations like: asked to write a model card; document a models intended use and limitations; prepare an AI model for review/launch.
How do I install Model Card in Claude Code?
Run `npx skills add mohitagw15856/pm-claude-skills --skill model-card -a claude-code`. Or copy the skill folder (skills/model-card in mohitagw15856/pm-claude-skills) into .claude/skills/model-card in your project. Claude Code loads it when a task matches its description.
How do I install Model Card in Codex?
Run `npx skills add mohitagw15856/pm-claude-skills --skill model-card -a codex`. Or copy the skill folder (skills/model-card in mohitagw15856/pm-claude-skills) into .agents/skills/model-card in your project. Codex loads it when a task matches its description.
Can I use Model Card 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 mohitagw15856/pm-claude-skills --skill model-card -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/model-card, .gemini/skills/model-card, .github/skills/model-card and .opencode/skills/model-card in your project.
What does Model Card need to run?
SKILL.md names no scripts, command-line tools or credentials: Model Card is instructions for the agent only.
Does Model Card 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 Model Card 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. Review the folder before installing.
What licence does Model Card use?
Model Card 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 Model Card use?
About 1k tokens (SKILL.md is roughly 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 Model Card?
Skills that share tags, products or a category with Model Card: LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), SageMaker Serving Image Selection (huggingface/skills, 11k stars), Hugging Face Local Model Evals (huggingface/skills, 11k stars) and Upload Post Image (huggingface/blog, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Model Card?
mohitagw15856 (a GitHub user) maintains it in mohitagw15856/pm-claude-skills, which has 1,434 GitHub stars. The repository holds 1,348 skills in this directory. The repository was last updated on October 9, 2026.
Source: mohitagw15856/pm-claude-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.