mirror of https://github.com/alirezarezvani/claude-skills.git synced 2026-08-28 04:24:58 +00:00

fix: rename all remaining built-in-shadowing skill names and harden the last cp1252-fatal scripts (#885 , #969 follow-through)

Round-2 sweep after re-auditing all 15 reported issues against the merged dev:

- #885 generalized: the original fix only renamed self-improving-agent's
  status/review, but three more plugins shipped skills whose bare names
  shadow Claude Code built-ins. Renamed with the same convention:
  playwright-pro init/review -> pw-init/pw-review, agenthub init/status ->
  hub-init/hub-status, autoresearch-agent status/resume -> ar-status/
  ar-resume. All command references (/pw: /hub: /ar:), docs, audit records,
  harness manifests, and mirror trees/indexes updated; the flat mirror
  namespace no longer collides on 'status'. New scripts/check_skill_names.py
  gate (wired into ci-quality-gate.yml as blocking) fails CI on any future
  bare reserved name; rule added to SKILL-AUTHORING-STANDARD.md.
- #969 follow-through: five more scripts print box-drawing characters that
  cannot exist in cp1252 (api_scorecard, api_linter,
  breaking_change_detector, humanizer_scorer, content_scorer) — same
  guarded UTF-8 reconfigure applied; all smoke-tested under a forced
  legacy encoding.

Verified: check_skill_names (incl. negative test), check_plugin_json,
check_paths, derive_counters, check_dual_publish, smoke_scripts (634/634),
0 broken mirror symlinks.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Qgc6RYXWJPr5oW9DHU7zR4

2026-08-21 08:38:50 +00:00

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Autoresearch Agent — Claude Code Instructions

This plugin runs autonomous experiment loops that optimize any file by a measurable metric.

Commands

Use the /ar: namespace for all commands:

/ar:setup — Set up a new experiment interactively
/ar:run — Run a single experiment iteration
/ar:loop — Start an autonomous loop with user-selected interval
/ar:ar-status — Show dashboard and results
/ar:ar-resume — Resume a paused experiment

How it works

You (the AI agent) are the experiment loop. The scripts handle evaluation and git rollback.

You edit the target file with ONE change
You commit it
You call run_experiment.py --single — it evaluates and prints KEEP/DISCARD/CRASH
You repeat

Results persist in results.tsv and git log. Sessions can be resumed.

When to use each command

Starting fresh

/ar:setup

Creates the experiment directory, config, program.md, results.tsv, and git branch.

Running one iteration at a time

/ar:run engineering/api-speed

Read history, make one change, evaluate, report result.

Autonomous background loop

/ar:loop engineering/api-speed

Prompts for interval (10min, 1h, daily, weekly, monthly), then creates a recurring job.

Checking progress

/ar:ar-status

Shows the dashboard across all experiments with metrics and trends.

Resuming after context limit or break

/ar:ar-resume engineering/api-speed

Reads results history, checks out the branch, and continues where you left off.

Agents

experiment-runner: Spawned for each loop iteration. Reads config, results history, decides what to try, edits target, commits, evaluates.

Key principle

One change per experiment. Measure everything. Compound improvements.

The agent never modifies the evaluator. The evaluator is ground truth.

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