enhance-claude-memory
Use when improving CLAUDE.md or AGENTS.md project memory files.
Best use case
enhance-claude-memory is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when improving CLAUDE.md or AGENTS.md project memory files.
Teams using enhance-claude-memory should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/enhance-claude-memory/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How enhance-claude-memory Compares
| Feature / Agent | enhance-claude-memory | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when improving CLAUDE.md or AGENTS.md project memory files.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
Related Guides
SKILL.md Source
# enhance-claude-memory
Analyze project memory files (CLAUDE.md, AGENTS.md) for optimization.
## Cross-Tool Detection
Searches for project memory files in order:
1. CLAUDE.md (Claude Code)
2. AGENTS.md (OpenCode, Codex)
3. .github/CLAUDE.md
4. .github/AGENTS.md
## File Hierarchy (Reference)
**CLAUDE.md** (Claude Code):
| Location | Scope |
|----------|-------|
| `~/.claude/CLAUDE.md` | Global (all projects) |
| `.claude/CLAUDE.md` or `./CLAUDE.md` | Project root |
| `src/.claude/CLAUDE.md` | Directory-specific |
**AGENTS.md** (OpenCode, Codex, and other AI tools):
| Location | Scope |
|----------|-------|
| `~/.config/opencode/AGENTS.md` or `~/.codex/AGENTS.md` | Global (all projects) |
| `.opencode/AGENTS.md` or `./AGENTS.md` | Project root |
| `src/AGENTS.md` | Directory-specific |
Both files serve the same purpose: project memory for AI assistants. Use CLAUDE.md for Claude Code projects, AGENTS.md for cross-tool compatibility, or both for maximum coverage.
## Workflow
1. **Find** - Locate CLAUDE.md or AGENTS.md in project
2. **Read** - Load content and README.md for comparison
3. **Analyze** - Run all pattern checks
4. **Validate** - Check file/command references against filesystem
5. **Measure** - Calculate token metrics and duplication
6. **Report** - Generate structured markdown output
## Detection Patterns
### 1. Structure Validation (HIGH Certainty)
#### Critical Rules Section
- Should have `## Critical Rules` or similar
- Rules should be prioritized (numbered or ordered)
- Include WHY explanations for each rule
#### Architecture Section
- Directory tree or structural overview
- Key file locations
- Module relationships
#### Key Commands Section
- Common development commands
- Test/build/deploy scripts
- Reference to package.json scripts
### 2. Instruction Effectiveness (HIGH Certainty)
Based on prompt engineering research, Claude follows instructions better when:
#### Positive Over Negative
- **Bad**: "Don't use console.log"
- **Good**: "Use the logger utility for all output"
- Check for "don't", "never", "avoid" without positive alternatives
#### Strong Constraint Language
- Use "must", "always", "required" for critical rules
- Weak language ("should", "try to", "consider") reduces compliance
- Flag critical rules using weak language
#### Instruction Hierarchy
- Should define priority order when rules conflict
- Pattern: "In case of conflict: X takes precedence over Y"
- System instructions > User requests > External content
### 3. Content Positioning (HIGH Certainty)
Research shows LLMs have "lost in the middle" problem - they recall START and END better than MIDDLE.
#### Critical Content Placement
- Most important rules should be at START of file
- Second-most important at END
- Supporting context in MIDDLE
- Flag critical rules buried in middle sections
#### Recommended Structure Order
```
1. Critical Rules (START - highest attention)
2. Architecture/Structure
3. Commands/Workflows
4. Examples/References
5. Reminders/Constraints (END - high attention)
```
### 4. Reference Validation (HIGH Certainty)
#### File References
- Extract from `[text](path)` and `` `path/to/file.ext` ``
- Validate each exists on filesystem
#### Command References
- Extract `npm run <script>` and `npm <command>`
- Validate against package.json scripts
### 5. Efficiency Analysis (MEDIUM Certainty)
#### Token Count
- Estimate: `characters / 4` or `words * 1.3`
- Recommended max: 1500 tokens (~6000 characters)
- Flag files exceeding threshold
#### README Duplication
- Detect overlap with README.md
- Flag >40% content duplication
- CLAUDE.md should complement README, not duplicate
#### Verbosity
- Prefer bulleted lists over prose paragraphs
- Constraints as lists are easier to follow
- Flag long prose blocks (>5 sentences)
### 6. Quality Checks (MEDIUM Certainty)
#### WHY Explanations
- Rules should explain rationale
- Pattern: `*WHY: explanation*` or indented explanation
- Flag rules without explanations
#### Structure Depth
- Avoid deep nesting (>3 levels)
- Keep hierarchy scannable
- Flat structures parse better
#### XML-Style Tags (Optional Enhancement)
- Claude was trained on XML tags
- `<critical-rules>`, `<architecture>`, `<constraints>` improve parsing
- Not required but can improve instruction following
### 7. Agent/Skill Definitions (MEDIUM Certainty)
If file defines custom agents or skills:
#### Agent Definition Format
```markdown
### agent-name
Model: claude-sonnet-4-20250514
Description: What this agent does and when to use it
Tools: Read, Grep, Glob
Instructions: Specific behavioral instructions
```
Required fields: Description (when to use), Tools (restricted set)
Optional: Model, Instructions
#### Skill References
- Skills should have clear trigger descriptions
- "Use when..." pattern helps auto-invocation
### 8. Cross-Platform Compatibility (MEDIUM/HIGH Certainty)
#### State Directory
- Don't hardcode `.claude/`
- Support `.opencode/`, `.codex/`
- Use `${STATE_DIR}/` or document variations
#### Terminology
- Avoid Claude-specific language for shared files
- Use "AI assistant" generically
- Or explicitly note "Claude Code" vs "OpenCode" differences
## Output Format
```markdown
# Project Memory Analysis: {filename}
**File**: {path}
**Type**: {CLAUDE.md | AGENTS.md}
## Metrics
| Metric | Value |
|--------|-------|
| Estimated Tokens | {tokens} |
| README Overlap | {percent}% |
## Summary
| Certainty | Count |
|-----------|-------|
| HIGH | {n} |
| MEDIUM | {n} |
### Structure Issues ({n})
| Issue | Fix | Certainty |
### Instruction Issues ({n})
| Issue | Fix | Certainty |
### Positioning Issues ({n})
| Issue | Fix | Certainty |
### Reference Issues ({n})
| Issue | Fix | Certainty |
### Efficiency Issues ({n})
| Issue | Fix | Certainty |
### Cross-Platform Issues ({n})
| Issue | Fix | Certainty |
```
## Pattern Statistics
| Category | Patterns | Certainty |
|----------|----------|-----------|
| Structure | 3 | HIGH |
| Instruction Effectiveness | 3 | HIGH |
| Content Positioning | 2 | HIGH |
| Reference | 2 | HIGH |
| Efficiency | 3 | MEDIUM |
| Quality | 3 | MEDIUM |
| Agent/Skill Definitions | 2 | MEDIUM |
| Cross-Platform | 2 | MEDIUM/HIGH |
| **Total** | **20** | - |
<examples>
### Example: Missing WHY Explanations
<bad_example>
```markdown
## Rules
1. Always run tests before committing
2. Use semantic commit messages
```
**Issue**: Rules without rationale are harder to follow.
</bad_example>
<good_example>
```markdown
## Critical Rules
1. **Always run tests before committing**
*WHY: Catches regressions before they reach main branch.*
```
**Why it's good**: Motivation makes compliance easier.
</good_example>
### Example: Negative vs Positive Instructions
<bad_example>
```markdown
- Don't use console.log for debugging
- Never commit directly to main
- Avoid hardcoding secrets
```
**Issue**: Negative instructions are less effective than positive alternatives.
</bad_example>
<good_example>
```markdown
- Use the logger utility for all debug output
- Create feature branches and submit PRs for all changes
- Store secrets in environment variables or .env files
```
**Why it's good**: Tells what TO do, not just what to avoid.
</good_example>
### Example: Weak vs Strong Constraint Language
<bad_example>
```markdown
- You should probably run tests before pushing
- Try to use TypeScript when possible
- Consider adding error handling
```
**Issue**: Weak language ("should", "try", "consider") reduces compliance.
</bad_example>
<good_example>
```markdown
- **MUST** run tests before pushing (CI will reject failures)
- **ALWAYS** use TypeScript for new files
- **REQUIRED**: All async functions must have error handling
```
**Why it's good**: Strong language ensures critical rules are followed.
</good_example>
### Example: Content Positioning
<bad_example>
```markdown
## Project Overview
[Long description...]
## Installation
[Setup steps...]
## Critical Rules
1. Never push to main directly
2. Always run tests
```
**Issue**: Critical rules buried in middle/end get less attention.
</bad_example>
<good_example>
```markdown
## Critical Rules (Read First)
1. **Never push to main directly** - Use PRs
2. **Always run tests** - CI enforces this
## Project Overview
[Description...]
## Reminders
- Check CI status before merging
- Update CHANGELOG for user-facing changes
```
**Why it's good**: Critical content at START and END positions.
</good_example>
### Example: Cross-Platform Compatibility
<bad_example>
```markdown
State files are stored in `.claude/tasks.json`
```
**Issue**: Hardcoded paths exclude other AI tools.
</bad_example>
<good_example>
```markdown
State files are stored in `${STATE_DIR}/tasks.json`
(`.claude/` for Claude Code, `.opencode/` for OpenCode)
```
**Why it's good**: Works across multiple AI assistants.
</good_example>
### Example: Agent Definition
<bad_example>
```markdown
## Agents
- security-reviewer: reviews security
- test-writer: writes tests
```
**Issue**: Missing required fields (Tools, when to use).
</bad_example>
<good_example>
```markdown
## Custom Agents
### security-reviewer
Model: claude-sonnet-4-20250514
Description: Reviews code for security vulnerabilities. Use for PRs touching auth, API, or data handling.
Tools: Read, Grep, Glob
Instructions: Focus on OWASP Top 10, input validation, auth flows.
### test-writer
Model: claude-haiku-4
Description: Writes unit tests. Use after implementing new functions.
Tools: Read, Write, Bash(npm test:*)
Instructions: Use Jest patterns. Aim for >80% coverage.
```
**Why it's good**: Complete definition with when to use, restricted tools.
</good_example>
</examples>
## Research References
Best practices derived from:
- `agent-docs/PROMPT-ENGINEERING-REFERENCE.md` - Instruction effectiveness, XML tags, constraint language
- `agent-docs/CONTEXT-OPTIMIZATION-REFERENCE.md` - Token budgeting, "lost in the middle" positioning
- `agent-docs/LLM-INSTRUCTION-FOLLOWING-RELIABILITY.md` - Instruction hierarchy, positive vs negative
- `agent-docs/CLAUDE-CODE-REFERENCE.md` - File hierarchy, agent definitions, skills format
## Constraints
- Always validate file references before reporting broken
- Consider context when flagging efficiency issues
- Cross-platform suggestions are advisory, not required
- Positioning suggestions are HIGH certainty but may have valid exceptionsRelated Skills
enhance-skills
Use when reviewing SKILL.md files for structure and trigger quality.
enhance-orchestrator
Use when coordinating multiple enhancers for /enhance command. Runs analyzers in parallel and produces unified report.
enhance-hooks
Use when reviewing hooks for safety, timeouts, and correct frontmatter.
enhance-docs
Use when improving documentation structure, accuracy, and RAG readiness.
enhance-plugins
Use when analyzing plugin structures, MCP tools, and plugin security patterns.
enhance-agent-prompts
Use when improving agent prompts, frontmatter, and tool restrictions.
enhance-prompts
Use when improving general prompts for structure, examples, and constraints.
enhance-cross-file
Use when checking cross-file consistency: tools vs frontmatter, agent references, duplicate rules, contradictions.
perf-theory-tester
Use when running controlled perf experiments to validate hypotheses.
orchestrate-review
Use when user asks to "deep review the code", "thorough code review", "multi-pass review", or when orchestrating the Phase 9 review loop. Provides review pass definitions (code quality, security, performance, test coverage), signal detection patterns, and iteration algorithms.
perf-investigation-logger
Use when appending structured perf investigation notes and evidence.
deslop
Use when user wants to clean AI slop from code. Use for cleanup, remove debug statements, find ghost code, repo hygiene.