Agent skill

Auto Improve

by crimeacs in crimeacs/auto-improve

GAN-style iterative improvement loop for any text artifact. An agent skill from crimeacs/auto-improve.

MITAuto-check passedEducation

Install Auto Improve

skills CLI
$ npx skills add crimeacs/auto-improve --skill auto-improve -a claude-code

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

GitHub CLI
$ gh skill install crimeacs/auto-improve auto-improve --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
auto-improve
GitHub stars
135
Token cost
~651 tokens
SKILL.md length
246 words
Files
57 (incl. assets)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

GAN-style iterative improvement loop for any text artifact. An agent skill from crimeacs/auto-improve.

  • Works in 3 steps: Mutate — best-of-N candidate edits,… → Score — each candidate graded against… → Decide — the best candidate is…
  • The user wants to autonomously improve the quality of a document
  • SKILL.md covers When to use, Run it, How it decides (the anti-slop… and Writing the rubric, plus 1 more section
  • Calls python3 and git; reaches aistudio.google.com; needs GEMINI_API_KEY

What it does

Auto Improve is an agent skill from crimeacs/auto-improve. GAN-style iterative improvement loop for any text artifact. Mutates a file, grades each change against a rubric with a SEPARATE model, keeps only verified wins (pairwise-judged), reverts the rest. The git history is the improvement log. Use when the user wants to autonomously improve the quality of a document, email, prompt, landing page, README, contract, or any text file.

Its SKILL.md is about 650 tokens, which your agent loads only when the skill is triggered. The skill folder holds 59 other files, including assets (for example `.github/CODE_OF_CONDUCT.md`, `.github/CONTRIBUTING.md` and `.github/ISSUE_TEMPLATE/bug_report.yml`).

It sits in Education, covering Quizzes and assessments, Git workflow and Landing pages. It works with Python, Google Gemini and Rust. The repository describes itself as: GAN-style self-improvement loop for any text artifact: mutate, grade with a SEPARATE model, keep only verified wins (pairwise-judged), revert the rest. The git history is the… The licence is MIT.

When your agent uses it

  • The user wants to autonomously improve the quality of a document
  • Tasks that involve Quizzes and assessments
  • Tasks that involve Git workflow

Example prompts

  • “/auto-improve”

Requirements

  • Python 3
  • A credential in GEMINI_API_KEY

Workflow steps

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

  1. Mutate — best-of-N candidate edits, applied as surgical diffs (crash-proof).
  2. Score — each candidate graded against the rubric by a separate model call.
  3. Decide — the best candidate is pairwise-judged against the champion (both

What it can do on your machine

Read from SKILL.md and the folder at commit 03aa5a9. 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:

    • python3
    • git

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Hosts in commands or code, which the agent is likely to contact:

    • aistudio.google.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • GEMINI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Auto Improve loads about 651 tokens when it runs. Until then it costs about 97 tokens; SKILL.md has 246 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~651

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

The full file from crimeacs/auto-improve at commit 03aa5a9, republished under its MIT licence (© crimeacs). 246 words, ~651 tokens.

Download SKILL.mdSave it as .claude/skills/auto-improve/SKILL.md (or your agent's skills folder). This skill also uses 56 other files; get the full folder from GitHub.
name
auto-improve
description
GAN-style iterative improvement loop for any text artifact. Mutates a file, grades each change against a rubric with a SEPARATE model, keeps only verified wins (pairwise-judged), reverts the rest. The git history is the improvement log. Use when the user wants to autonomously improve the quality of a document, email, prompt, landing page, README, contract, or any text file.
user-invocable
true

auto-improve

Autonomous, judge-gated self-improvement for any text artifact. See README.md for the full guide; this is the agent-facing quick reference.

When to use

The user wants something measurably better, not just rewritten — and is willing to express "better" as a rubric. Good fits: cold emails, landing copy, prompts, skill definitions, blog posts, cover letters, docs, contracts, menus.

Run it

bash
export GEMINI_API_KEY=...        # https://aistudio.google.com/apikey
python3 improve.py \
  --artifact path/to/file.md \   # must be inside a git repo
  --tag v1 \                     # → branch improve/v1, results/v1.tsv
  --max-iterations 8 \
  --criteria path/to/rubric.md   # OPTIONAL — omit to auto-infer a rubric; or add
                                 # --goal "what good looks like" to steer the inferred one

If you don't pass --criteria, auto-improve writes a rubric from the artifact first and saves it to results/<tag>.rubric.md — read it to see what it's optimizing for. Check a finished run: python3 improve.py --status --tag v1. The result lives on the improve/<tag> git branch — git diff main improve/v1 -- <file>.

How it decides (the anti-slop part)

  1. Mutate — best-of-N candidate edits, applied as surgical diffs (crash-proof).
  2. Score — each candidate graded against the rubric by a separate model call.
  3. Decide — the best candidate is pairwise-judged against the champion (both orderings, debiased); kept only if it genuinely wins, else reverted.

The mutator never grades its own work, and confident-but-worse rewrites are discarded — so the climb is real and every commit is a verified gain.

Writing the rubric

A markdown file of weighted dimensions totaling 100 — anchored (50/70/90), reward-framed, specific. See criteria/README.md and the worked examples in criteria/.

Key rules

  • The mutator and evaluator never share context.
  • One artifact, one rubric, one --tag per run.
  • The git branch is the source of truth; results/<tag>.tsv is the climb log (untracked).
  • Never edit outside the artifact; small surgical diffs, not wholesale rewrites.

© crimeacs, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 56 other files (assets) in the repository root of crimeacs/auto-improve.

  • SKILL.md
  • .editorconfig
  • .github/CODEOWNERS
  • .github/CODE_OF_CONDUCT.md
  • .github/CONTRIBUTING.md
  • .github/ISSUE_TEMPLATE/bug_report.yml
  • .github/ISSUE_TEMPLATE/config.yml
  • .github/ISSUE_TEMPLATE/feature_request.yml
  • .github/PULL_REQUEST_TEMPLATE.md
  • .github/SECURITY.md
  • .github/SUPPORT.md
  • .github/dependabot.yml
  • .github/workflows/ci.yml
  • .gitignore
  • .pre-commit-config.yaml
  • CHANGELOG.md
  • CITATION.cff
  • LICENSE
  • … and 39 more

Open the folder on GitHubat commit 03aa5a9

Compare with similar skills

Auto Improve 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.

Auto Improve compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Auto Improve this skillcrimeacs/auto-improve135—~651Automated safety check: PassMIT
Nxvutensils/nxv136—~7.9kAutomated safety check: NotesMIT
New Pattern Authoring WorkflowTotoro-jam/battle-tested-patterns344—~1.5kAutomated safety check: PassMIT
Comment Judgefmflurry/settings-opencode171—~2.5kAutomated safety check: PassMIT
Generating Documentationancoleman/ai-design-components526—~3kAutomated safety check: PassMIT
Writing Code CommentsPostHog/posthog40k—~1.6kAutomated safety check: PassCustom licence

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Questions about Auto Improve

What does Auto Improve do?

GAN-style iterative improvement loop for any text artifact. An agent skill from crimeacs/auto-improve. Auto Improve is an agent skill from crimeacs/auto-improve. GAN-style iterative improvement loop for any text artifact.

When should I use Auto Improve?

Auto Improve fits situations like: the user wants to autonomously improve the quality of a document; tasks that involve Quizzes and assessments; tasks that involve Git workflow.

How do I install Auto Improve in Claude Code?

Run `npx skills add crimeacs/auto-improve --skill auto-improve -a claude-code`. Or copy the skill folder (the crimeacs/auto-improve repository) into .claude/skills/auto-improve in your project. Claude Code loads it when a task matches its description.

How do I install Auto Improve in Codex?

Run `npx skills add crimeacs/auto-improve --skill auto-improve -a codex`. Or copy the skill folder (the crimeacs/auto-improve repository) into .agents/skills/auto-improve in your project. Codex loads it when a task matches its description.

Can I use Auto Improve 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 crimeacs/auto-improve --skill auto-improve -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/auto-improve, .gemini/skills/auto-improve, .github/skills/auto-improve and .opencode/skills/auto-improve in your project.

What does Auto Improve need to run?

Going by SKILL.md and its folder, Auto Improve needs the command-line tools its instructions call (python3 and git) and credentials named GEMINI_API_KEY. Our summary lists: Python 3; A credential in GEMINI_API_KEY.

Does Auto Improve access the network?

SKILL.md names 1 domain. In commands or code: aistudio.google.com; the agent is likely to contact it when it follows the instructions. This is read from the text; nothing was executed.

Is Auto Improve 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 Auto Improve use?

Auto Improve is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Auto Improve use?

About 651 tokens (SKILL.md is roughly 2.6k 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 Auto Improve?

Skills that share tags, products or a category with Auto Improve: Nxv (utensils/nxv, 136 stars), New Pattern Authoring Workflow (Totoro-jam/battle-tested-patterns, 344 stars), Comment Judge (fmflurry/settings-opencode, 171 stars) and Generating Documentation (ancoleman/ai-design-components, 526 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Auto Improve?

crimeacs (a GitHub user) maintains it in crimeacs/auto-improve, which has 135 GitHub stars. The repository was last updated on August 3, 2026.

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