A small, opinionated collection of Claude Code slash commands, skills, and CLI tools I actually use.

Everything here is MIT-licensed. Grab what's useful; ignore the rest.

git clone [email protected]:STRML/cc-skills.git

Then symlink (or copy) what you want into your Claude Code config:

# Slash commands → ~/.claude/commands/
ln -s "$(pwd)/cc-skills/commands/code-cleanup.md" ~/.claude/commands/code-cleanup.md

# Skills → ~/.claude/skills/
ln -s "$(pwd)/cc-skills/skills/scan-diff" ~/.claude/skills/scan-diff

Slash commands become available immediately. Skills require a session restart to appear in the Skill tool list.

commands/   Slash commands — invoke with /<name>
skills/     Skills — invoke via the Skill tool

Deep codebase cleanup via eight parallel subagents that inherit this session's context. Recon happens in the current conversation; the eight forks see it as live history, so there's no need to inline a brief. Each fork owns one concern:

1. Deduplicate repeated logic (DRY where it cuts complexity)
2. Consolidate shared type definitions
3. Remove dead code (knip, vulture, cargo machete, etc.)
4. Break circular dependencies (madge, pydeps)
5. Replace weak types (any, unknown, interface{}) with real ones
6. Strip defensive programming that hides errors instead of handling them
7. Delete deprecated code, compat shims, and orphaned feature flags
8. Remove AI slop — narration comments, stubs, commented-out code

The command offers an edit mode (make high-confidence fixes in place) and a dry-run mode (evidence-backed reports only, reconcile with human triage). Dry-run is the safer default for fragile or first-time codebases. Dispatch uses the built-in subagent_type: "fork" (Claude Code ≥ 2.1.229); older versions fall back to the Agent-tool + cached-prefix recipe.

Fetch and address comments on the current branch's PR. Handles CodeRabbit, Claude-bot, and human reviewers differently. Verifies findings against current code before fixing.

Bootstrap a project for Claude Code — analyze the repo, write CLAUDE.md with commands and conventions, and optionally scaffold .devcontainer/devcontainer.json with a language-detected base image.

Search past Claude Code session history via search-sessions. Supports metadata queries (instant), full-content deep search, date filters, and project filters. Use when you need to find what was done in a previous session.

After a hard-won fix, capture the root cause and solution into project memory where future sessions auto-load it. Runs two parallel research subagents, then writes a structured memory/solution_<slug>.md and updates the MEMORY.md index.

End-of-session skill that updates the project's CLAUDE.md with lessons learned — non-obvious commands, corrections, gotchas. Fires on /clear, PreCompact, or explicit invocation. Filters out generic advice and obvious conventions.

Quick bug-scan pass on the current git diff via a focused Haiku subagent. Targets logic errors, null access, auth bypasses, race conditions. Skips style and formatting. Not a replacement for full review — a cheap first filter.

Filter a PR's CodeRabbit comments to only those added since a given commit. Cuts through re-shown stale comments so you only triage what's actually new.

Pre-commit verification workflow. Checks for pre-commit hooks first (skips redundant runs), reviews git status and git diff, catches debug code and secrets, stages selectively, and writes a structured Conventional-Commits-style message. Pushes only on explicit request.

Screenshot-driven loop for CSS/UI work. Forces a "before" screenshot baseline, then iterates: change → screenshot → compare → confirm. Prevents blind edits and the "I think it should look better now" failure mode. Includes responsive-breakpoint verification.

A live HTML dashboard for long agent runs: an epic, a PR landing queue, hours of autonomous work. scripts/dash.py is the only writer (locked, atomic, safe for a main session and subagents at once); dash.py serve puts the page on 127.0.0.1 and it refreshes every 10 seconds. It shows task progress with a dependency-driven Flow panel, open questions (each with the default the agent proceeds on, newest first, answered ones folded away), blockers, deliverables, two metric tiles and an activity log. Answers typed on the page come back to the agent on its next dash.py command. State lives in <repo>/.dashboard/ and stays out of git. Standard library Python 3, no dependencies.

PRs welcome. One skill or command per PR, please. Each addition should include a short rationale in the description — what problem it solves, what it doesn't try to do.

MIT