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braincandy-parallelbraincandy-parallel/tamarindos-workflow-kit/skills/auto-research/SKILL.md

auto-research

Skill0 starsChanged 55 days agoNo licenceView on GitHub

Autonomous skill optimization system that iteratively improves Claude Code skills by running binary eval suites, mutating instruction bodies via Opus, scoring variants against baselines, and promoting winners. Use this skill when the user says "auto-research", "optimize skill", "improve skill", "run skill optimization", "sweep skills", "optimize my skills", "self-improve", or wants to run the auto-research optimization loop. Also trigger on "/auto-research" with any arguments.

10 other projects use a version of this.

Adopted by

Most recently taken up by

Used with

Projects with it also use compare-screenshots, marketing-pages and 10 more.

Other files people use alongside this one.

Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
  • transitive-bullshitSkill

    compare-screenshots

    Compare screenshots against the intended design, distinguishing approved references from historical baselines. Use for iterative implementation matching, before/after visual review, objective image telemetry, or checking a lone capture for flat, empty, or badly framed content.

    Also in 5 projects that use this

  • dzhngSkill

    marketing-pages

    Best-practice rulebook for a marketing site's pages, organized by page class — campaign landers, product pages, programmatic SEO trees, editorial. Use when writing or updating a landing/marketing page, wiring a campaign lander to an attribution identifier, changing site-wide nav/footer links, touching sitemap/robots/agent-readable surfaces, or auditing a public site's indexing, reachability, and conversion setup.

    Also in 4 projects that use this

  • dzhngSkill

    close-spec

    When a spec under specs/<feature>/ is done shipping (a write-spec build, or any planned task that produced a spec), archive it to specs/done/ and rewrite it from a build-plan into a durable rationale — the why, the principles, the invariants — pointing back to the real code for the how. Use when implementation has landed and the plan no longer matches what shipped, or the user says a feature/spec is finished. Pairs with [write-spec](../write-spec/SKILL.md) (the plan this closes) and [review](../review/SKILL.md) (run before closing).

    Also in 4 projects that use this

  • LucasMatuszewskiSkill

    audit-agents

    Audit and maintain agent configuration files (.claude/agents, AGENTS.md, CLAUDE.md, agent-memory). Checks for duplicates, outdated info, naming conflicts, wrong technical facts, and files over 200 lines. Fixes all issues and commits.

    Also in 4 projects that use this

  • isLinXuSkill

    eval-skills

    AI Agent Skill unit testing framework. A framework-agnostic toolkit for discovering, scaffolding, selecting, evaluating, and reporting on AI skills. Use this skill to assess skill quality before production, compare candidate skills on the same benchmark, enforce quality gates in CI/CD, and generate human-readable evaluation reports.

    Also in 5 projects that use this

  • gastonsalgSkill

    write-skills

    Creates effective Claude Code skills following official Anthropic guidelines and community best practices. Use when creating or refactoring skills. Focuses on WHAT not HOW, proper structure, and addressing real failure modes.

    Also in 5 projects that use this

  • +6 more from dzhng

The file

We split this skill into the rules it gives an agent

11 rules. 0 are common, 2 are distinctive, and 9 are very specific to this project.

  • 0

    Common

    Most of the 10 edited versions we read keep these.

  • 2

    Distinctive

    This author's own choices. Worth a look.

  • 9

    Very specific

    Tied to their project's names, files or tools. Probably skip.

No licence file, so all rights are reserved — read it at the source. We count its rules but don't quote them. Read them on GitHub.

“Common” is measured: kept by at least 6 in 10 of the 10 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

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What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

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