run-benchmark

run-benchmark is a cursor rule for Cursor from danielvm-git/bigpowers. It costs 53 tokens per session (1,102 once invoked), scanned A, original, MIT.

A benchmark runner for measuring how much a coding skill improves an agent's results. It compares runs with and without the skill and separates practice cases from held-out validation cases.

In plain words
What is it for?
It is for running repeated capability tests, calculating pass@k—the chance that at least one of several attempts passes—and producing benchmark reports.
Why use it?
It helps detect regressions and prevents a skill from appearing successful only because it was tuned to the examples used during development.

Cursor rule for Cursor

Written for Cursor: installed under .cursor/. Also seen: mentions CLAUDE.md.

Needs its repository: it runs a file that does not travel with it, so clone the repository first. The line is bash scripts/run-benchmark.sh <skill-name> # benchmark single skill.

Good fit It is for running repeated capability tests, calculating pass@k—the chance that at least one of several attempts passes—and producing benchmark reports.

Compare 6 cursor rules from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/danielvm-git/bigpowers
agentmods
npx agentmods add rules/danielvm-git/bigpowers/run-benchmark

Made for: Cursor.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for run-benchmark

README.md
[![agentmods](https://agentmods.dev/badge/rules/danielvm-git/bigpowers/run-benchmark/github.svg)](https://agentmods.dev/rules/danielvm-git/bigpowers/run-benchmark)
Your own site
<a href="https://agentmods.dev/rules/danielvm-git/bigpowers/run-benchmark"><img src="https://agentmods.dev/badge/rules/danielvm-git/bigpowers/run-benchmark/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for run-benchmark

Your own site · 80×15
<a href="https://agentmods.dev/rules/danielvm-git/bigpowers/run-benchmark"><img src="https://agentmods.dev/badge/rules/danielvm-git/bigpowers/run-benchmark.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 53 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,102 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00053 $0.01102
Opus 5.5 $0.00021 $0.00441
Sonnet 5.5 $0.00011 $0.00220
Haiku 4.5 $0.00005 $0.00110

Measured 1mo ago against content hash 01cd876b512d, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

run-benchmark scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.cursor/rules/run-benchmark.mdc · 85 lines

How it starts

The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Run Benchmark

HARD GATE — Do NOT use benchmark scores to declare a skill "good" or "bad" in isolation. Benchmarks measure relative quality vs. a baseline — they catch regressions, they do not certify correctness.

Reads benchmark definitions from specs/benchmarks/, executes each scenario's grader with and without the skill loaded, and writes a structured pass@k report with delta grading that evolve-skill consumes.

With/Without-Skill Delta Grading

Every scenario runs N times (default 3) in two modes: with the skill loaded and without (bare agent with only CLAUDE.md). The delta Δ = pass@k_with − pass@k_without isolates the skill's causal contribution. A negative delta is a regression flag.

Train/Validation Split

Benchmark definitions partition scenarios into two sets:

Set Tag Purpose
Train split: train Development scenarios — used while iterating. Hitting 100% on train is expected.
Validation split: validation Held-out scenarios — the real quality signal. Overfitting train while validation stagnates is a design smell.

pass@k is reported separately for train and validation. Validation score is authoritative; train score is iteration guidance only.

Usage

bash scripts/run-benchmark.sh <skill-name>           # benchmark single skill
bash scripts/run-benchmark.sh --all                  # benchmark all with definitions
bash scripts/run-benchmark.sh <skill-name> --baseline # pin results as baseline

Process

  1. Locate definition — Read specs/benchmarks/<skill>.yaml. If absent, stop with message.

  2. Partition scenarios — Split by split field (train → iteration, validation → authoritative, default: validation).

  3. Run each scenario (N-run delta) — For each scenario, run grader N times (default 3, configurable via runs:):

    • Without skill: Agent with only CLAUDE.md/CONVENTIONS.md
    • With skill: Agent with the skill under test active
    • Code grader: bash -c <command>, exit 0 → PASS. Timeout: 15s.
    • Rubric grader: yes/no per criterion, ≥ 80% yes → PASS.
    • Record: {scenario_id: {with: [P/F,...], without: [P/F,...]}}

Read the full file on GitHub · 85 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 1mo ago First seen · 85 lines · 53 tokens per session scan A 01cd876b512d

Subscribe to this mod's changes

run-benchmark is a cursor rule published in the GitHub repository danielvm-git/bigpowers (267 stars, last pushed 27d ago), licensed MIT. It adds 53 tokens to every session and 1,102 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.