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.
Builds an eval plan for an AI feature - error analysis on real traces, failure-mode ranking, code checks and binary LLM judges validated against human labels, CI tests, production monitoring, and a…
Install Eval Plan
$ npx skills add menkesu/awesome-pm-skills --skill eval-plan -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install menkesu/awesome-pm-skills eval-plan --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/menkesu/awesome-pm-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/eval-plan .claude/skills/eval-plan && 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 "eval-plan" agent skill from https://github.com/menkesu/awesome-pm-skills/tree/main/skills/eval-plan into .claude/skills/eval-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-plan", 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/menkesu/awesome-pm-skills/tree/main/skills/eval-planType 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 menkesu/awesome-pm-skills --skill eval-plan -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install menkesu/awesome-pm-skills eval-plan --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/menkesu/awesome-pm-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/eval-plan .agents/skills/eval-plan && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "eval-plan" agent skill from https://github.com/menkesu/awesome-pm-skills/tree/main/skills/eval-plan into .agents/skills/eval-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-plan", 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 menkesu/awesome-pm-skills --skill eval-plan -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install menkesu/awesome-pm-skills eval-plan --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/menkesu/awesome-pm-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/eval-plan .cursor/skills/eval-plan && 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 "eval-plan" agent skill from https://github.com/menkesu/awesome-pm-skills/tree/main/skills/eval-plan into .cursor/skills/eval-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-plan", 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/menkesu/awesome-pm-skills.git --path skills/eval-plan--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 menkesu/awesome-pm-skills --skill eval-plan -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install menkesu/awesome-pm-skills eval-plan --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/menkesu/awesome-pm-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/eval-plan .gemini/skills/eval-plan && 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 "eval-plan" agent skill from https://github.com/menkesu/awesome-pm-skills/tree/main/skills/eval-plan into .gemini/skills/eval-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-plan", 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 menkesu/awesome-pm-skills eval-planInstalls 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 menkesu/awesome-pm-skills --skill eval-plan -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/menkesu/awesome-pm-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/eval-plan .github/skills/eval-plan && 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 "eval-plan" agent skill from https://github.com/menkesu/awesome-pm-skills/tree/main/skills/eval-plan into .github/skills/eval-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-plan", 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 menkesu/awesome-pm-skills --skill eval-plan -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install menkesu/awesome-pm-skills eval-plan --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/menkesu/awesome-pm-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/eval-plan .opencode/skills/eval-plan && 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 "eval-plan" agent skill from https://github.com/menkesu/awesome-pm-skills/tree/main/skills/eval-plan into .opencode/skills/eval-plan/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "eval-plan", 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
eval-plan- GitHub stars
- 433
- Token cost
- ~4.5k tokens
- SKILL.md length
- 2,544 words
- Files
- 4 (incl. references, assets)
- Skills in repo
- 25
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Builds an eval plan for an AI feature - error analysis on real traces, failure-mode ranking, code checks and binary LLM judges validated against human labels, CI tests, production monitoring, and a…
- Works in 3 steps: Diagnose (ask before answering) → Pick the play → Run it
- You ask how do we eval this
- SKILL.md covers When to use, Step 1 - Diagnose (ask before…, Step 2 - Pick the play and Step 3 - Run it, plus 6 more sections
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
What it does
Eval Plan is an agent skill from menkesu/awesome-pm-skills. Builds an eval plan for an AI feature - error analysis on real traces, failure-mode ranking, code checks and binary LLM judges validated against human labels, CI tests, production monitoring, and a launch bar. Use when you ask how do we eval this, how do I test an AI feature, our LLM outputs are inconsistent, are the evals good enough, LLM-as-judge, hallucinations, or what accuracy is good enough to launch. Draws on 41 Lenny's Podcast guests incl. Hamel Husain, Shreya Shankar and Sander Schulhoff.
Its SKILL.md is about 4.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files and assets (for example `references/frameworks.md` and `references/quotes.md`).
It sits in AI & LLM Engineering, covering LLM evaluation and Podcasting. The repository describes itself as: Product management workflows grounded in Lenny's Podcast, for Claude Code, Codex, and Cursor.
When your agent uses it
- You ask how do we eval this
- How do I test an AI feature
- Our LLM outputs are inconsistent
- Are the evals good enough
Example prompts
- “Use the eval-plan skill to build an eval plan for an AI feature - error analysis on real traces, failure-mode ranking, code checks and binary LLM…”
- “/eval-plan”
Workflow steps
3 steps, taken from the step headings in SKILL.md.
- Diagnose (ask before answering)
- Pick the play
- Run it
What it can do on your machine
Read from SKILL.md and the folder at commit c1b6e2d. 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 (its code samples are markdown).
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
Eval Plan loads about 4.5k tokens when it runs, and up to ~9.3k if it reads all its reference files. Until then it costs about 128 tokens; SKILL.md has 2,544 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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 2,544 words (~4,500 tokens).
“Turn a vague 'the AI feels off' into a ranked list of failure modes, a small set of trustworthy evaluators, and a CI + monitoring plan you can paste into a doc. Built from 169 insights from 41 Lenny's Podcast…”
- name
- eval-plan
Files
SKILL.md and 3 other files (references, assets) in skills/eval-plan of menkesu/awesome-pm-skills.
- SKILL.md
- assets/card.png
- references/frameworks.md
- references/quotes.md
Open the folder on GitHubat commit c1b6e2d
Compare with similar skills
Eval Plan 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 |
|---|---|---|---|---|---|---|
| Eval Plan this skillmenkesu/awesome-pm-skills | 433 | — | ~4.5k | Automated safety check: Pass | Custom licence | |
| LLM Benchmarking with lm-evaluation-harnessOrchestra-Research/AI-Research-SKILLs | 13k | 8 repos | ~3k | Automated safety check: Pass | MIT | |
| Hugging Face Local Model Evalshuggingface/skills | 11k | 2 repos | ~1.6k | Automated safety check: Pass | Apache-2.0 | |
| Looperksimback/looper | 710 | — | ~2.7k | Automated safety check: Notes | MIT | |
| Agent Eval Engineeringlangchain-ai/langchain-skills | 1.3k | — | ~4k | Automated safety check: Pass | MIT | |
| Quality FlywheelGoogleCloudPlatform/vertex-ai-samples | 792 | — | ~2k | Automated safety check: Pass | Apache-2.0 |
Similar skills
- Official
Hugging Face Local Model Evals
huggingface/skills
Runs evaluations of Hugging Face Hub models on local hardware with inspect-ai or lighteval, and helps choose between vLLM, Transformers and accelerate backends.
Looper
ksimback/looper
Scaffold a well-designed agent loop with best-practice coaching and a cross-model review council.
- Official
Agent Eval Engineering
langchain-ai/langchain-skills
Builds agent evaluations in stages: inspect the repository and traces, agree a Task Spec with you, then build, audit and run a Harbor task with an independent verifier.
Quality Flywheel
GoogleCloudPlatform/vertex-ai-samples
Evaluate and improve GenAI models and agents using the Google GenAI Evaluation SDK.
Eval Harness
cloudnative-co/claude-code-starter-kit
Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles.
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Questions about Eval Plan
What does Eval Plan do?
Builds an eval plan for an AI feature - error analysis on real traces, failure-mode ranking, code checks and binary LLM judges validated against human labels, CI tests, production monitoring, and a…. Eval Plan is an agent skill from menkesu/awesome-pm-skills. Builds an eval plan for an AI feature - error analysis on real traces, failure-mode ranking, code checks and binary LLM judges validated against human labels, CI tests, production monitoring, and a launch bar.
When should I use Eval Plan?
Eval Plan fits situations like: you ask how do we eval this; how do I test an AI feature; our LLM outputs are inconsistent; are the evals good enough.
How do I install Eval Plan in Claude Code?
Run `npx skills add menkesu/awesome-pm-skills --skill eval-plan -a claude-code`. Or copy the skill folder (skills/eval-plan in menkesu/awesome-pm-skills) into .claude/skills/eval-plan in your project. Claude Code loads it when a task matches its description.
How do I install Eval Plan in Codex?
Run `npx skills add menkesu/awesome-pm-skills --skill eval-plan -a codex`. Or copy the skill folder (skills/eval-plan in menkesu/awesome-pm-skills) into .agents/skills/eval-plan in your project. Codex loads it when a task matches its description.
Can I use Eval Plan 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 menkesu/awesome-pm-skills --skill eval-plan -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/eval-plan, .gemini/skills/eval-plan, .github/skills/eval-plan and .opencode/skills/eval-plan in your project.
What does Eval Plan need to run?
SKILL.md names no scripts, command-line tools or credentials: Eval Plan is instructions for the agent only.
Does Eval Plan 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 Eval Plan 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 Eval Plan use?
Eval Plan has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Eval Plan use?
About 4.5k tokens (SKILL.md is roughly 18k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.8k tokens, read only when the agent opens those files.
What are the alternatives to Eval Plan?
Skills that share tags, products or a category with Eval Plan: LLM Benchmarking with lm-evaluation-harness (Orchestra-Research/AI-Research-SKILLs, 13k stars), Hugging Face Local Model Evals (huggingface/skills, 11k stars), Looper (ksimback/looper, 710 stars) and Agent Eval Engineering (langchain-ai/langchain-skills, 1.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Eval Plan?
menkesu (a GitHub user) maintains it in menkesu/awesome-pm-skills, which has 433 GitHub stars. The repository holds 25 skills in this directory. The repository was last updated on October 6, 2026.
Source: menkesu/awesome-pm-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.