evolution-status

A command that displays success and failure statistics for learning skills and ranks which ones are the best candidates for improvement. The statistics come from recorded skill usage and outcomes.

In plain words
What is it for?
Use it to inspect usage, successes, failures, failure rates, and optimization priorities, or to view the underlying JSON data.
Why use it?
It shows where optimization effort is most justified instead of relying on intuition about which skill needs work.

Command

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 commands/okdk7788/skill-evolution/evolution-status
Clone the repo
git clone --depth 1 https://github.com/okdk7788/skill-evolution
Per session 23 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 291 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00023 $0.00291
Opus 5 $0.00012 $0.00146
Sonnet 5 $0.00005 $0.00058
Haiku 4.5 $0.00002 $0.00029

Measured yesterday against content hash 1de0dbcbfeed, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

evolution-status 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 yesterday.

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.

plugins/skill-evolution/commands/evolution-status.md · 21 lines

What it actually says

학습 스킬들의 진화 상태 — 사용 빈도 대비 실패율로 어떤 스킬을 다듬을 가치가 큰지 보여줍니다.

다음을 실행하고 결과를 사용자에게 그대로 보여주세요:

python3 "${CLAUDE_PLUGIN_ROOT}/scripts/evolution_report.py"

읽는 법:

  • use — self-improving-skills 텔레메트리 기준 사용 횟수.
  • ok/fail — skill-evolution이 Stop 훅에서 수집한 성공/실패 outcome.
  • fail% — 실패율. priority — 사용량 가중 × 스무딩된 실패율(높을수록 최적화 우선).
  • *opt — 이미 /optimize-skill 로 최적화된 적 있는 스킬.

1순위 후보가 있으면 사용자에게 /optimize-skill <name> 실행을 제안하세요. outcome이 아직 없으면(신선한 설치) "스킬이 실제로 쓰이면서 Stop 훅이 돌면 데이터가 쌓인다"고 안내하세요.

$ARGUMENTS 에 json 이 오면 evolution_report.py json 으로 원본 데이터를 보여주세요.

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. yesterday First seen · 21 lines · 23 tokens per session scan A 1de0dbcbfeed

Subscribe to this mod's changes

evolution-status is a command published in the GitHub repository okdk7788/skill-evolution (1 stars, last pushed 1mo ago), licensed MIT. It adds 23 tokens to every session and 291 once invoked, about $0.0001 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 2026-08-31.