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config-gc

Garbage collection for your Claude Code configuration. Periodically scans ~/.claude (skills, memory, hooks, permissions, MCP servers, caches) for redundant, stale, orphaned, or low-value items, then walks the user through a confirm-each-deletion cleanup. Use when the user says

O que é config-gc?

config-gc is a Claude Code agent skill that garbage collection for your Claude Code configuration. Periodically scans ~/.claude (skills, memory, hooks, permissions, MCP servers, caches) for redundant, stale, orphaned, or low-value items, then walks the user through a confirm-each-deletion cleanup. Use when the user says.

Funciona comClaude Code~Codex CLI~Cursor
npx skills add https://github.com/affaan-m/everything-claude-code/tree/main/skills/config-gc

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Documentação

Config GC — Garbage Collection for Claude Code Setups

Borrowed from runtime garbage collection: periodically scan for objects that are no longer referenced, redundant, expired, or low-value, and reclaim the space. The critical difference: here, collection requires a human in the loop. Never delete autonomously.

When to Activate

  • The user asks to clean up, audit, or slim down their Claude Code configuration
  • The user complains about too many skills, noisy hooks, or slow session startup
  • A monthly/periodic config review is due
  • After installing a large skill pack (e.g. this repo), to reconcile overlaps with existing setup

Do NOT activate for: cleaning project source code (that's refactoring), clearing chat history, or uninstalling Claude Code itself.

Design Philosophy

  1. Append-only configs leak. Skills, memory files, hooks, and permission entries only ever get added. Without periodic review they rot silently.
  2. Regular audits beat one-time purges. Scan every ~30 days, propose a small batch of candidates each time.
  3. Per-channel strategies. Each accumulation type (skills, hooks, permissions, ...) has its own staleness signals — don't apply one rule everywhere.
  4. Soft-delete first. Rename to .disabled > move to ~/.claude/_gc_trash/ > real deletion. Always keep an undo path.
  5. Forced human-in-the-loop. Every candidate gets its own [y/n/skip] confirmation. No "yes to all" shortcut.
  6. Keep a log. Every GC run appends to ~/.claude/gc_log.md: what was touched, why, and how to undo it.

Scan Channels

#ChannelPathStaleness / redundancy signals
1Skills~/.claude/skills/*/Heavily overlapping names; never triggered in recent transcripts; domain mismatch with the user's actual work; broken or empty SKILL.md
2Memory~/.claude/**/memory/*.md + its indexMultiple index entries for one topic; contents contradicting newer entries; dates that have passed; orphan files missing from the index; sub-100-word fragments that should merge
3Hooks~/.claude/hooks/ + settingsScripts present on disk but referenced by no hook config; old versions superseded by rewrites
4Permissionspermissions.allow in settings.json / settings.local.jsonDuplicate entries; specific entries already covered by a wildcard (e.g. Bash(git push) when Bash(*) is allowed); one-off grants from past experiments
5MCP servers~/.claude.json or project .mcp.jsonServers that fail to connect; functional duplicates; long-unused
6Scheduled reminders / jobswherever the user keeps themFired one-shots older than 30 days; jobs whose target scripts no longer exist
7Project history~/.claude/projects/*/Stale handoff snapshots; session records superseded by newer state
8Runtime cachescache/, file-history/, logs/, shell-snapshots/Sort by size and mtime; propose items >30 days old and large

Workflow

  1. Scan all channels (or the subset the user names). Collect candidates with: path, channel, signal that flagged it, size, last-modified.
  2. Rank by confidence (broken/orphaned = high; merely old = low) and present as a numbered table. Cap each run at ~20 candidates — GC is periodic, not exhaustive.
  3. Confirm one by one. For each candidate show the evidence, then ask [y/n/skip]. The user can stop at any point.
  4. Soft-delete confirmed items: prefer .disabled rename for skills/hooks and _gc_trash/<date>/ move for files. Permission entries live in JSON (no comments possible): back up the settings file, record each removed entry verbatim in gc_log.md, then remove it from the allow array with jq. Only hard-delete when the user explicitly asks.
  5. Log the run to ~/.claude/gc_log.md: timestamp, items actioned, undo instructions.
  6. Report: reclaimed size, channels still healthy, suggested next review date.

Example Scan Commands

Orphaned hook scripts (channel 3) — scripts on disk that no hook config references:

for f in ~/.claude/hooks/*; do
  name=$(basename "$f")
  grep -rq "$name" ~/.claude/settings.json ~/.claude/settings.local.json 2>/dev/null \
    || echo "ORPHAN: $f"
done

Redundant permission entries (channel 4) — duplicates, and specific grants shadowed by a wildcard:

jq -r '.permissions.allow[]' ~/.claude/settings.local.json | sort | uniq -d
if jq -e '.permissions.allow | index("Bash(*)")' ~/.claude/settings.local.json >/dev/null; then
  jq -r '.permissions.allow[]' ~/.claude/settings.local.json \
    | grep '^Bash(' | grep -vF 'Bash(*)'
fi

Largest stale caches (channel 8) — du -k instead of GNU-only find -printf, so it works on macOS/BSD too:

find ~/.claude/file-history ~/.claude/shell-snapshots -type f -mtime +30 \
  -exec du -k {} + 2>/dev/null | sort -rn | head -20

Soft-delete with undo path (capture the date once so the log can't disagree with the directory):

gc_date=$(date +%Y-%m-%d)
mkdir -p ~/.claude/_gc_trash/$gc_date
mv ~/.claude/skills/dead-skill ~/.claude/_gc_trash/$gc_date/
echo "$(date -Iseconds) moved skills/dead-skill -> _gc_trash/$gc_date/ (undo: mv back)" >> ~/.claude/gc_log.md

Removing a confirmed-redundant permission entry (JSON has no comments — back up, log, then edit):

cp ~/.claude/settings.local.json ~/.claude/settings.local.json.bak
echo "$(date -Iseconds) removed permission entry: Bash(git push) (undo: restore from .bak or re-add)" >> ~/.claude/gc_log.md
jq '.permissions.allow -= ["Bash(git push)"]' ~/.claude/settings.local.json.bak \
  > ~/.claude/settings.local.json

Anti-Patterns

  • Bulk approval. Asking "delete all 15? [y/n]" defeats the design. One item, one decision.
  • Hard-deleting on first pass. If there's no _gc_trash/ copy or .disabled rename, you did it wrong.
  • Treating "old" as "dead". A skill untouched for 60 days may be seasonal (tax season, quarterly reviews). Age is a signal, not a verdict — that's why a human confirms.
  • Cleaning memory by truncation. Merging two contradicting memory files requires reading both and keeping the newer truth, not deleting the longer one.
  • Touching anything outside ~/.claude (or the project's .claude/). Config GC never wanders into source trees.

Best Practices

  • Run after big additions, not just on a calendar: installing a 50-skill pack is exactly when overlap with existing skills appears.
  • When two skills overlap, prefer disabling the one with the weaker trigger description — it's the one that was probably never firing anyway.
  • Permission cleanup is the highest-value channel per minute spent: redundant allow-entries make security review harder.
  • Keep gc_log.md forever. It's tiny, and "when did I disable that hook and why" comes up more often than you'd think.

Related Skills

  • skill-stocktake — audits skill quality; config-gc audits skill existence. Run stocktake on what survives GC.
  • workspace-surface-audit — the additive counterpart: recommends what to install. config-gc is the subtractive half of the same lifecycle.
  • configure-ecc — after installing skills with it, run config-gc to reconcile overlaps with your pre-existing setup.
  • continuous-learning — produces the memory files this skill later audits.
  • security-review — pairs well with the permissions channel.

Individual skills in this repo

This repo contains 20 individual skills — each has its own dedicated page.

accessibility

Design, implement, and audit inclusive digital products using WCAG 2.2 Level AA. Use when building or auditing UI that must meet WCAG 2.2 Level AA, or when reviewing a change for keyboard, contrast, or screen-reader support.

affaan-m/claude-api

Anthropic Claude API patterns for Python and TypeScript. Covers Messages API, streaming, tool use, vision, extended thinking, batches, prompt caching, and Claude Agent SDK. Use when building applications with the Claude API or Anthropic SDKs.

affaan-m/everything-claude-code

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/everything-claude-code-conventions

Development conventions and patterns for everything-claude-code. JavaScript project with conventional commits.

affaan-m/frontend-design

Create distinctive, production-grade frontend interfaces with high design quality. Use when the user asks to build web components, pages, or applications and the visual direction matters as much as the code quality.

affaan-m/gget

gget CLI and Python workflow for quick genomic database queries, sequence lookup, BLAST-style searches, enrichment checks, and reproducible bioinformatics evidence logs.

affaan-m/literature-review

Systematic literature-review workflow for academic, biomedical, technical, and scientific topics, including search planning, source screening, synthesis, citation checks, and evidence logging.

affaan-m/motion-ui

Production-ready UI motion system for React/Next.js. Use when implementing animations, transitions, or motion patterns.

affaan-m/project-guidelines-example

Example project-specific skill template based on a real production application.

affaan-m/pubmed-database

Direct PubMed and NCBI E-utilities search workflows for biomedical literature, MeSH queries, PMID lookup, citation retrieval, and API-backed literature monitoring.

affaan-m/scholar-evaluation

Structured scholarly-work evaluation for papers, proposals, literature reviews, methods sections, evidence quality, citation support, and research-writing feedback.

affaan-m/uspto-database

USPTO patent and trademark data workflow for official record lookup, PatentSearch queries, TSDR checks, assignment data, and reproducible IP research logs.

agent-architecture-audit

Full-stack diagnostic for agent and LLM applications. Audits the 12-layer agent stack for wrapper regression, memory pollution, tool discipline failures, hidden repair loops, and rendering corruption. Produces severity-ranked findings with code-first fixes. Essential for developers building agent applications, autonomous loops, or any LLM-powered feature. Use when an agent or LLM feature misbehaves and the failing layer is unknown, or before shipping an agent stack.

agent-eval

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics. Use when choosing between coding agents, or when a change to an agent setup needs measured pass rate, cost, and time rather than an impression.

agent-harness-construction

Design and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates. Use when defining or revising an agent

agentic-engineering

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model routing. Use when planning or executing engineering work that agents will carry out end to end.

agentic-os

Build persistent multi-agent operating systems on Claude Code. Covers kernel architecture, specialist agents, slash commands, file-based memory, scheduled automation, and state management without external databases. Use when building a persistent multi-agent system on Claude Code with its own memory, commands, and scheduling.

agent-introspection-debugging

Structured self-debugging workflow for AI agent failures using capture, diagnosis, contained recovery, and introspection reports. Use when an agent run fails and you need a reproducible diagnosis instead of a retry.

agent-payment-x402

Add x402 payment execution to AI agents with per-task budgets, spending controls, and non-custodial wallets. Supports Base through agentwallet-sdk and X Layer through OKX Payments / OKX Agent Payments Protocol. Use when an agent must pay for something itself and needs per-task budgets, spending controls, and a non-custodial wallet.

agent-self-evaluation

Use after completing any non-trivial task. The agent self-rates its output on 5 axes — accuracy, completeness, clarity, actionability, conciseness — with concrete evidence per criterion. Produces a structured 1-5 scorecard with specific improvement suggestions.

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