evolve-skill

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods

npx agentmods add rules/danielvm-git/bigpowers/evolve-skill

Clone the repo

git clone --depth 1 https://github.com/danielvm-git/bigpowers

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.

README.md

[![agentmods](https://agentmods.dev/badge/rules/danielvm-git/bigpowers/evolve-skill.svg)](https://agentmods.dev/rules/danielvm-git/bigpowers/evolve-skill)

Your own site

<a href="https://agentmods.dev/rules/danielvm-git/bigpowers/evolve-skill"><img src="https://agentmods.dev/badge/rules/danielvm-git/bigpowers/evolve-skill.svg" alt="Measured on agentmods" height="20"></a>

Per session 48 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.

When invoked 623 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 0 findings. Scan, not verified.

Origin unknown 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.

Model	Per session	Once invoked
Fable 5	$0.00048	$0.00623
Opus 5	$0.00024	$0.00311
Sonnet 5	$0.00010	$0.00125
Haiku 4.5	$0.00005	$0.00062

Measured today against content hash 90f9fe347559, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

evolve-skill 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 today.

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/evolve-skill.mdc · 55 lines

How it starts

The opening of the file, as written. The whole thing — 55 lines — stays where its author put it; the contents beside it link to each section on GitHub.

story: e23s03

story: e09s01

story: e09s05

Evolve Skill

HARD GATE — No skill change ships without benchmark score ≥ pre-change baseline. Learning is measured and versioned — never implicit.

Loop

Regression gate — Run bash scripts/run-verification-gates.sh to catch mechanical regressions (compliance, sync pipeline, size budget) before spending time on benchmark evals. If golden suite fails, fix regressions first — they are pre-requisites for any capability improvement.
Establish baseline — Run run-benchmark <skill> --baseline. If no definition exists at specs/benchmarks/<skill>.yaml, create one following specs/benchmarks/SCHEMA.md first. Save report path in state.yaml. If specs/benchmarks/reports/BASELINE-<skill>.yaml already exists, skip this step.
Identify gap — Read the baseline report (specs/benchmarks/reports/BASELINE-<skill>.yaml). Find scenarios with result: FAIL or low pass_at_k. This is the measurable gap.
plan-work — Write a minimal change proposal targeting the failing scenarios. Include verify commands.
Edit via craft-skill / direct SKILL.md edit; run bash scripts/sync-skills.sh.
Re-run benchmark — run-benchmark <skill>. Compare new pass_at_k against baseline.
- IMPROVED or STABLE → advance to step 6.
- REGRESSION (new pass_at_k < baseline) → revert the change and loop back to step 3.
Record decision — Write specs/adr/NNNN-evolve-<skill>.md with before/after pass_at_k scores. Update session-state.

Verify

→ verify: test -d specs/benchmarks && test -f skills/run-benchmark/SKILL.md

See REFERENCE.md for ADR template.

Evolve Skill — ADR snippet

## ADR-XXXX: Evolve &lt;skill-name&gt;

**Status:** Accepted
**Benchmark:** before X% / after Y%
**Change:** one-sentence summary
**Evidence:** path/to/benchmark-report.md

Benchmark repo: bigpowers-benchmark — resolve the local clone on this machine; clone it from wherever your fork lives if absent. Never assume a hard-coded absolute path or a specific owner.

Read the full file on GitHub · 55 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.

today First seen · 55 lines · 48 tokens per session scan A 90f9fe347559

Subscribe to this mod's changes

evolve-skill is a cursor rule published in the GitHub repository danielvm-git/bigpowers (162 stars, last pushed 2d ago), licensed MIT. It adds 48 tokens to every session and 623 once invoked, about $0.0002 per session on Opus 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.

Planning ai-agents automation bmad claude-code clean-code cursor-rules

Getting it into your agent

Wrote this? Show the measurements

What it costs to keep this loaded

Grade A, and why

Nothing flagged

How it starts

story: e23s03

story: e09s01

story: e09s05

Evolve Skill

Loop

Verify

Evolve Skill — ADR snippet

What this file has done since we first saw it

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