audit-memory
Audit Claude Code CLAUDE.md memory files for quality, compliance, and organization. Use to validate import syntax, detect circular imports, and check hierarchy compliance.
What this skill does
# Audit Memory Command Audit Claude Code CLAUDE.md memory files for quality, compliance, and organization. ## Initialization Before auditing, initialize the environment: Get the current UTC date, capture the project root path, ensure the temp directory exists, and clean up stale audit files. The `memory-management` skill provides authoritative validation guidance (auto-loaded when this command runs). ## What Gets Audited - Import syntax (`@path/to/file.md`) - Hierarchy compliance (enterprise > project > user) - Circular import detection - Size guidelines and progressive disclosure - Content organization ## Command Arguments | Argument | Description | | --- | --- | | *(none)* | Audit all discoverable CLAUDE.md files | | `project` | Only audit project-level files | | `user` | Only audit `~/.claude/CLAUDE.md` | | `all` | Audit all scopes explicitly | | `--force` | Audit regardless of modification status | | `--skip-validation` | Skip finding validation (faster, but may include false positives) | | `--token-budget` | Run ONLY token budget analysis (skip full audit) | ## Step 1: Discover CLAUDE.md Files Check root `CLAUDE.md`, `.claude/CLAUDE.md`, user `~/.claude/CLAUDE.md` (Unix) or `%USERPROFILE%\.claude\CLAUDE.md` (Windows), and `.claude/memory/*.md`. Build list with scope and level (root/dot-claude/memory/user). ## Step 2: Parse Arguments Parse scope selector and `--force` flag. Filter files to match requested scope. ## Step 3: Present Audit Plan Display mode, files discovered, primary files, and imported memory files. ## Step 4: Execute Audits For each file, spawn the `memory-component-auditor` subagent with scope, level, path, and last audit date. Run in parallel batches of 3-5. After individual audits, perform cross-file circular import detection by building an import graph. Subagents write findings to `.claude/temp/`. The main conversation thread collects results and updates audit logs using its Write/Edit tools. ## Step 4.5: Validate Findings **Unless `--skip-validation` flag is present:** 1. Spawn the `audit-finding-validator` agent with: - `project_root`: The captured project root path - `audit_type`: "memory" - `audit_files`: List of `.claude/temp/audit-*-memory-*.json` file paths 2. Wait for validation to complete 3. Read updated JSON files with validation results 4. Filter out FALSE_POSITIVE findings completely before aggregation 5. Note: Filtered findings are logged to `.claude/temp/audit-filtered-findings.json` **If `--skip-validation` flag is present:** - Skip validation phase entirely (current speed preserved) - Present all findings without filtering - Note in summary: "Validation: Skipped" ## Step 5: Final Summary Report total audited by scope, results, circular import check, and details tables. Provide remediation steps for issues. **Include validation statistics (if validation was performed):** - Validation performed: Yes/No - Findings validated: X - False positives filtered: Y - Verified findings: Z - Unverified findings: W ## Step 6: Token Budget Analysis (included by default) **Scope:** Only always-loaded files (root CLAUDE.md + files with @-prefix imports marked as "Always-loaded") **Note:** Use `--token-budget` to run ONLY this step (skips Steps 1-5 full audit). ### 6.1 Fetch Official Guidance Invoke `memory-management` skill (which delegates to `docs-management`) to fetch current official guidance on memory file sizing. Official docs recommend keeping memory "concise and focused" with progressive disclosure - specific token thresholds are repo-specific standards, not official requirements. ### 6.2 Calculate Tokens Per File For each always-loaded file: 1. Read file content 2. Estimate tokens: `len(content) / 4` (approximate for English markdown) 3. Extract declared Token Budget from header if present (e.g., `**Token Budget:** ~1,800 tokens`) 4. Record file path, actual tokens, declared budget ### 6.3 Calculate Aggregate Total Sum all always-loaded file tokens. Do NOT include on-demand files (those without @ prefix in root, or marked "Context-Dependent"). ### 6.4 Evaluate Against Repo-Specific Thresholds **These thresholds are repo-specific standards (see audit-framework.md), NOT from official Claude Code docs:** | Status | Token Range | Guidance | | --- | --- | --- | | PASS | ≤12k tokens | Within repo budget | | WARN | 12k-15k tokens | At upper limit, monitor | | FAIL | >15k tokens | Over budget, remediation needed | ### 6.5 Generate Report Report includes: 1. **Top 5 largest files** by token count with percentage of total 2. **Aggregate total** vs repo-specific budget 3. **Declared vs actual variance** for files where declared budget differs from actual by >20% 4. **Status** (PASS/WARN/FAIL) based on aggregate total ### 6.6 Suggest Remediation (if FAIL or WARN) If over budget, recommend: - Files that could move to on-demand loading (not critical for every session) - Large files (>2k tokens) that could be split using hub pattern - Reference progressive disclosure guidance from official docs (via memory-management skill) ### 6.7 Update Audit Log Add Token Budget Analysis section to `.claude/audit/memory.md` with: - Status and analysis date - Metrics table (total, budget, variance) - Top 5 largest files table - Declared vs actual variance table (if any discrepancies) ## Important Notes ### Import Syntax Valid: `@path/to/file.md` (e.g., `@.claude/memory/workflows.md`) ### Hierarchy Compliance 1. Enterprise (highest precedence) 2. Project root (`CLAUDE.md`) 3. Project dot-claude (`.claude/CLAUDE.md`) 4. User (`~/.claude/CLAUDE.md` - lowest) ### Size Guidelines | File Type | Recommended Size | | --- | --- | | Root CLAUDE.md | < 50 lines core + imports | | Memory imports | < 500 lines each | ### Cross-Platform Paths | Platform | User Memory | | --- | --- | | Unix | `~/.claude/CLAUDE.md` | | Windows | `%USERPROFILE%\.claude\CLAUDE.md` | ## Audit Log Location All audit results are written to `.claude/audit/memory.md`. Use `/audit-log memory` to view current audit status. ## Example Usage ### Example 1: Audit All Memory Files ```text User: /audit-memory Claude: Discovering CLAUDE.md files... ## Audit Plan **Mode**: SMART **Files discovered**: 12 ### Primary Files: 1. [project:root] CLAUDE.md 2. [user] ~/.claude/CLAUDE.md ### Imported Files: 3. [project:memory] .claude/memory/workflows.md ... [Spawns memory-component-auditor subagents] ## Audit Complete **Circular Import Check**: ✓ No cycles detected | Scope | File | Result | Score | | --- | --- | --- | --- | | project | CLAUDE.md | PASS | 100/100 | ``` ### Example 2: Audit Project Only ```text User: /audit-memory project Claude: Auditing project-level files... ```
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.