audit-setup
Comprehensive audit of your Claude Code configuration — CLAUDE.md, skills, context files, settings, MCP configs, and hooks. Use when you want to clean up, deduplicate, or optimize your Claude Code setup. Invoke this skill whenever you mention auditing, reviewing, cleaning up, or optimising your Claude Code configuration, memory files, or instruction files.
What this skill does
Claude Code Setup Audit ======================= You are performing a comprehensive audit of the user's Claude Code configuration. The goal is to eliminate bloat, resolve conflicts, surface stale rules, and produce a prioritised changelist the user can act on. Phase 1: Discovery ------------------ Read everything before forming any opinions. Do not respond until you have completed this full scan. ### Scan these locations (in order): 1. **Project-level config** (`.claude/` in the current project root) - `CLAUDE.md` (project instructions) - `settings.json` - `skills/` (every SKILL.md and any bundled references) - `commands/` (slash commands) - `hooks/` - Any other `.md` or config files in `.claude/` 2. **Global config** (`~/.claude/`) - `CLAUDE.md` (global instructions) - `settings.json` - `skills/` (every SKILL.md and any bundled references) - `commands/` - `hooks/` 3. **MCP configuration** - `.mcp.json` in the project root - `~/.claude/mcp.json` (global MCP config) 4. **Other instruction files** - `.cursorrules`, `.windsurfrules`, or similar if present - Any `README.md` sections that appear to contain agent instructions - Any other `*.md` files in the project root that look like they contain rules or preferences Build a mental inventory of every rule, instruction, convention, and preference you find across all files before proceeding. Phase 2: Analysis ----------------- For **each** rule, instruction, or preference you found, evaluate it against these six questions: ### Q1 — Already Default Behaviour? Is this something Claude already does without being told? If Claude's base behaviour already covers it, the rule is dead weight consuming context tokens for no benefit. ### Q2 — Conflicts With Another Rule? Does this contradict or tension with another rule elsewhere in the setup? Pay special attention to conflicts **between layers** (global vs. project-level) since project-level should override global, but contradictions still cause confusion. ### Q3 — Redundant / Duplicate? Does this repeat something already covered by a different rule or file? Look for both exact duplicates and semantic duplicates (same intent, different wording). ### Q4 — Bandaid Fix? Does this read like it was added to fix one specific bad output rather than improve outputs overall? These tend to be overly narrow, reference a specific incident, or micromanage a single behaviour. ### Q5 — Too Vague to Be Actionable? Is this so vague that it would be interpreted differently on every invocation? Examples: "be more natural," "use a good tone," "write clean code," "be thorough." If you can't objectively verify compliance, the rule is noise. ### Q6 — Stale or Orphaned? Does this reference tools, file paths, frameworks, APIs, dependencies, or workflows that no longer exist in the project? Check whether referenced paths actually exist and whether mentioned tools are still configured. Phase 3: Token Cost Assessment ------------------------------ Estimate the approximate token cost of the user's full configuration (all loaded CLAUDE.md content, skill descriptions, and always-loaded instruction files). Note: - What percentage of the setup is actionable vs. dead weight - Which files or sections are the biggest offenders - Whether the skill description budget (~2% of context window) is being pressured Phase 4: Output --------------- Present your findings in this exact structure: ### 1. Setup Summary A brief overview of what you found: how many files, how many distinct rules/instructions, and the estimated token footprint. ### 2. Conflicts Between Files List every conflict found between any two files. For each conflict: - **File A**: [path] — the rule - **File B**: [path] — the contradicting rule - **Recommendation**: which to keep and why ### 3. Recommended Cuts A numbered list of everything you'd remove. For each item: - **Location**: file path and the specific rule - **Reason**: one-line explanation citing which question (Q1–Q6) it fails - **Impact**: low / medium / high (how much context is being wasted) Sort by impact (high first). ### 4. Recommended Merges Rules that aren't individually wrong but should be consolidated. For each: - **Rules to merge**: list the overlapping rules and their locations - **Proposed single rule**: the merged version ### 5. Recommended Rewrites Rules that have the right intent but are too vague, too narrow, or poorly worded. For each: - **Current**: the rule as-is - **Proposed**: the improved version - **Why**: what's better about the new version ### 6. Global vs. Project Layer Issues Any rules that are in the wrong layer (e.g., project-specific rules in global config, or generic preferences buried in a project-level file that should be global). ### 7. Changelist for CLAUDE.md Rather than a full rewrite, provide a **diff-style changelist**: - Lines/sections to **remove** (with reason) - Lines/sections to **merge** (with proposed replacement) - Lines/sections to **reword** (with proposed replacement) - Suggested **reordering** if the current structure buries important rules This applies to both global and project CLAUDE.md if both exist. Guidelines ---------- - Be direct. If a rule is useless, say so — the user asked for honesty. - Preserve intent. When proposing merges or rewrites, don't lose the user's actual preferences. - Respect layers. Global config = cross-project defaults. Project config = overrides for this specific codebase. - Don't invent new rules. Only work with what exists. - If a rule is good and well-written, skip it silently. Only surface problems. - When in doubt about whether something is "default behaviour," err on the side of keeping it — false positives are more annoying than a slightly heavy config.
Related in AI Agents
skill-development
IncludedComprehensive meta-skill for creating, managing, validating, auditing, and distributing Claude Code skills and slash commands (unified in v2.1.3+). Provides skill templates, creation workflows, validation patterns, audit checklists, naming conventions, YAML frontmatter guidance, progressive disclosure examples, and best practices lookup. Use when creating new skills, validating existing skills, auditing skill quality, understanding skill architecture, needing skill templates, learning about YAML frontmatter requirements, progressive disclosure patterns, tool restrictions (allowed-tools), skill composition, skill naming conventions, troubleshooting skill activation issues, creating custom slash commands, configuring command frontmatter, using command arguments ($ARGUMENTS, $1, $2), bash execution in commands, file references in commands, command namespacing, plugin commands, MCP slash commands, Skill tool configuration, or deciding between skills vs slash commands. Delegates to docs-management skill for official documentation.
reprompter
IncludedTransform messy prompts into well-structured, effective prompts — single or multi-agent. Use when: "reprompt", "reprompt this", "clean up this prompt", "structure my prompt", rough text needing XML tags and best practices, "reprompter teams", "repromptception", "run with quality", "smart run", "smart agents", multi-agent tasks, audits, parallel work, anything going to agent teams. Don't use when: simple Q&A, pure chat, immediate execution-only tasks. See "Don't Use When" section for details. Outputs: Structured XML/Markdown prompt, quality score (before/after), optional team brief + per-agent sub-prompts, agent team output files. Success criteria: Single mode quality score ≥ 7/10; Repromptception per-agent prompt quality score 8+/10; all required sections present, actionable and specific.
adaptive-compaction
IncludedAdaptive add-on policy and recovery layer that decides WHEN to compact, prune, snapshot, or fork -- replacing fixed-percent auto-compaction across Claude Code, Codex, and MCP-capable hosts. Trigger on auto-compact timing or damage: "when should I compact", "is it safe to compact now or start a fresh session", "auto-compact fires too early/mid-task", "switching to an unrelated task but the window still has space", "context rot", "answers get worse the longer the session runs", "the agent forgot the plan or my decisions after it summarized", "add a layer on top that manages context without changing the agent", raising autoCompactWindow to give the policy room, or installing/tuning a cross-tool compaction policy or PreCompact hook -- even when "compaction" is never said but the problem is context-window pressure or post-summarization memory loss. Do NOT use to summarize a conversation, build RAG, write a summarization prompt (decides WHEN not HOW), or answer max-context-length trivia.
agent-skill-creator
IncludedCreate cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.
llm-wiki
IncludedUse when building or maintaining a persistent personal knowledge base (second brain) in Obsidian where an LLM incrementally ingests sources, updates entity/concept pages, maintains cross-references, and keeps a synthesis current. Triggers include "second brain", "Obsidian wiki", "personal knowledge management", "ingest this paper/article/book", "build a research wiki", "compound knowledge", "Memex", or whenever the user wants knowledge to accumulate across sessions instead of being re-derived by RAG on every query.
skill-master
IncludedAgent Skills authoring, evaluation, and optimization. Create, edit, validate, benchmark, and improve skills following the agentskills.io specification. Use when designing SKILL.md files, structuring skill folders (references, scripts, assets), ingesting external documentation into skills, running trigger evals, benchmarking skill quality, optimizing descriptions, or performing blind A/B comparisons. Keywords: agentskills.io, SKILL.md, skill authoring, eval, benchmark, trigger optimization.