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Official agent skill

Benchmark Checklist

by cursor in cursor/plugins

Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it.

OfficialNo licenceAuto-check passed

Install Benchmark Checklist

skills CLI
$ npx skills add cursor/plugins --skill benchmark-checklist -a claude-code

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

GitHub CLI
$ gh skill install cursor/plugins benchmark-checklist --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/cursor/plugins.git skills-src && mkdir -p .claude/skills && cp -r skills-src/pstack/skills/benchmark-checklist .claude/skills/benchmark-checklist && 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
benchmark-checklist
GitHub stars
10k
Used in
3 other repos
Token cost
~1.4k tokens
SKILL.md length
893 words
Files
1
Skills in repo
99
Repo updated
First seen
Licence
None found

At a glance

Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it.

  • Works in 7 steps: Why not double? Name the limiter.… → Was it tuned? Run every side the way… → Did it break limits? Do the arithmetic.… → …
  • You run a benchmark
  • SKILL.md covers Before you run anything, The questions, Report and How this fits the other perf…
  • Calls node

What it does

Benchmark Checklist is an agent skill from cursor/plugins, published by the product's own GitHub organization. Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it. Use when you run a benchmark or report a speedup or regression you measured.

Its SKILL.md is about 1.4k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: Cursor plugin specification and official plugins.

When your agent uses it

  • You run a benchmark
  • Report a speedup
  • Regression you measured

Example prompts

  • “/benchmark-checklist”

Workflow steps

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

  1. Why not double? Name the limiter. Profile in a run you do not report, because profilers and tracers slow the work down. Use CPU per…
  2. Was it tuned? Run every side the way production runs it: release builds, production flags and env, batching and transaction settings…
  3. Did it break limits? Do the arithmetic. Compare bytes per second with disk and network bandwidth, and operations per second times the cost…
  4. Did it error? Count failures and non-success responses, and check that the outputs are correct, not just present. Errors behave…
  5. Does it reproduce? Run each side at least 5 times, and alternate the sides (A, B, A, B, and so on) so that warmup, lazy initialization…
  6. Does it matter? Next to any micro result, measure the end-to-end path a user waits on, with realistic data sizes and concurrency. Report…
  7. Did it even happen? Confirm the work ran inside the timed region. The request reached the server, the rows were written, the bytes were…

What it can do on your machine

Read from SKILL.md and the folder at commit 9f451cf. 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

    Shell commands in SKILL.md call:

    • node

    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

Benchmark Checklist loads about 1.4k tokens when it runs. Until then it costs about 61 tokens; SKILL.md has 893 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~61
When it runs · the whole SKILL.md, loaded when a task matches
~1.4k

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

Without a licence we can't republish the file, so here is its outline and opening line. It has 893 words (~1,352 tokens).

“Use this when you produce a performance number: a PR's before and after, a regression claim, a hillclimb harness, or a library or config choice. Explain the Number says why. Answer each question below with evidence from a run, not…”

— opening of SKILL.md by cursor
name
benchmark-checklist
disable-model-invocation
true

Read the full SKILL.md on GitHub

Files

Just SKILL.md in pstack/skills/benchmark-checklist of cursor/plugins.

Open the folder on GitHubat commit 9f451cf

Used in 3 other repositories

We found 3 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 3 other GitHub owners. This page covers the copy in cursor/plugins, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Benchmark Checklist 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.

Benchmark Checklist compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Benchmark Checklist this skillcursor/plugins10k3 repos~1.4kAutomated safety check: PassNone
Benchmarkaffaan-m/ECC274k3 repos~654Automated safety check: PassMIT
Benchmark TuneMesh-LLM/mesh-llm3.5k—~1.6kAutomated safety check: PassApache-2.0
Benchmarkaffaan-m/ECC274k—~412Automated safety check: PassMIT
Benchmarkaffaan-m/ECC274k—~330Automated safety check: PassMIT
Perf Benchmarkercomposio-community/awesome-claude-plugins1.9k—~269Automated safety check: PassNone

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  • Reflect on Session Learnings

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  • Technical Writing Standard

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  • Advisor Mode

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Questions about Benchmark Checklist

What does Benchmark Checklist do?

Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it. Benchmark Checklist is an agent skill from cursor/plugins, published by the product's own GitHub organization. Vet a perf measurement (limiter, tuning, limits, errors, repeatability, relevance, and whether the work happened) before you report or act on it.

When should I use Benchmark Checklist?

Benchmark Checklist fits situations like: you run a benchmark; report a speedup; regression you measured.

How do I install Benchmark Checklist in Claude Code?

Run `npx skills add cursor/plugins --skill benchmark-checklist -a claude-code`. Or copy the skill folder (pstack/skills/benchmark-checklist in cursor/plugins) into .claude/skills/benchmark-checklist in your project. Claude Code loads it when a task matches its description.

How do I install Benchmark Checklist in Codex?

Run `npx skills add cursor/plugins --skill benchmark-checklist -a codex`. Or copy the skill folder (pstack/skills/benchmark-checklist in cursor/plugins) into .agents/skills/benchmark-checklist in your project. Codex loads it when a task matches its description.

Can I use Benchmark Checklist 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 cursor/plugins --skill benchmark-checklist -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/benchmark-checklist, .gemini/skills/benchmark-checklist, .github/skills/benchmark-checklist and .opencode/skills/benchmark-checklist in your project.

What does Benchmark Checklist need to run?

Going by SKILL.md and its folder, Benchmark Checklist needs the command-line tools its instructions call (node).

Does Benchmark Checklist 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 Benchmark Checklist 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 Benchmark Checklist use?

No licence was found for Benchmark Checklist or its repository. Without one, default copyright applies: ask the author before reusing or redistributing it.

How many tokens does Benchmark Checklist use?

About 1.4k tokens (SKILL.md is roughly 5.4k 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 Benchmark Checklist?

Skills that share tags, products or a category with Benchmark Checklist: Benchmark (affaan-m/ECC, 274k stars), Benchmark Tune (Mesh-LLM/mesh-llm, 3.5k stars), Benchmark (affaan-m/ECC, 274k stars) and Benchmark (affaan-m/ECC, 274k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Benchmark Checklist?

cursor (a GitHub organization, an official publisher) maintains it in cursor/plugins, which has 10,130 GitHub stars. The repository holds 99 skills in this directory. The repository was last updated on October 6, 2026.

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