AI Newsletter Digest improvements: fixed QP soft line break decoding, URL extraction, and content cleaning

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# Reflect - Agent Self-Improvement Skill
> "Correct once, never again."
Transform your AI assistant into a continuously improving partner. The reflect skill analyzes conversations for corrections and successful patterns, permanently encoding learnings into agent definitions.
## Features
- **Signal Detection**: Automatically identifies corrections with confidence levels (HIGH/MEDIUM/LOW)
- **Category Classification**: Routes learnings to appropriate agent files (Code Style, Architecture, Process, Domain, Tools)
- **Skill Generation**: Creates new skills from non-trivial debugging discoveries
- **Metrics Tracking**: Quantifies improvement with acceptance rates and statistics
- **Human-in-the-Loop**: All changes require explicit approval
- **Git Integration**: Full version control with easy rollback
## Installation
### Via ClawdHub CLI
```bash
clawdhub install reflect
```
### Manual Installation
Copy the `reflect/` folder to your skills directory:
- Claude Code: `~/.claude/skills/reflect/`
- Clawdbot: `~/.clawdbot/skills/reflect/`
## Usage
### Basic Reflection
Just say "reflect" or "review session" to trigger analysis:
```
User: reflect
Agent: [Analyzes conversation, presents learnings for approval]
```
### Toggle Auto-Reflection
```
User: reflect on
Agent: Auto-reflection enabled. Will analyze before context compaction.
User: reflect off
Agent: Auto-reflection disabled.
```
### Check Status
```
User: reflect status
Agent:
Sessions analyzed: 42
Signals detected: 156
Changes accepted: 89 (78%)
Skills created: 5
```
### Review Pending
```
User: reflect review
Agent: [Shows low-confidence learnings awaiting validation]
```
## How It Works
1. **Scan**: Analyzes conversation for correction signals
2. **Classify**: Maps signals to categories and target files
3. **Propose**: Generates diffs for agent updates or new skills
4. **Review**: Presents changes for user approval
5. **Apply**: Commits approved changes with descriptive messages
## Signal Detection
| Confidence | Triggers | Examples |
|------------|----------|----------|
| HIGH | Explicit corrections | "never", "always", "wrong", "stop" |
| MEDIUM | Approved approaches | "perfect", "exactly", "that's right" |
| LOW | Observations | Patterns that worked, not validated |
## Configuration
Set custom state directory:
```bash
export REFLECT_STATE_DIR=/path/to/state
```
Default locations:
- `~/.reflect/` (portable)
- `~/.claude/session/` (Claude Code)
## License
MIT
## Author
Claude Code Toolkit

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---
name: reflect
description: Self-improvement through conversation analysis. Extracts learnings from corrections and success patterns, permanently encoding them into agent definitions. Philosophy - Correct once, never again.
version: "2.0.0"
user-invocable: true
triggers:
- reflect
- self-reflect
- review session
- what did I learn
- extract learnings
- analyze corrections
allowed-tools:
- Read
- Write
- Edit
- Grep
- Glob
- Bash
metadata:
clawdbot:
emoji: "🪞"
config:
stateDirs: ["~/.reflect"]
---
# Reflect - Agent Self-Improvement Skill
Transform your AI assistant into a continuously improving partner. Every correction becomes a permanent improvement that persists across all future sessions.
## Quick Reference
| Command | Action |
|---------|--------|
| `reflect` | Analyze conversation for learnings |
| `reflect on` | Enable auto-reflection |
| `reflect off` | Disable auto-reflection |
| `reflect status` | Show state and metrics |
| `reflect review` | Review pending learnings |
## When to Use
- After completing complex tasks
- When user explicitly corrects behavior ("never do X", "always Y")
- At session boundaries or before context compaction
- When successful patterns are worth preserving
## Workflow
### Step 1: Scan Conversation for Signals
Analyze the conversation for correction signals and learning opportunities.
**Signal Confidence Levels:**
| Confidence | Triggers | Examples |
|------------|----------|----------|
| **HIGH** | Explicit corrections | "never", "always", "wrong", "stop", "the rule is" |
| **MEDIUM** | Approved approaches | "perfect", "exactly", "that's right", accepted output |
| **LOW** | Observations | Patterns that worked but not explicitly validated |
See [data/signal_patterns.md](data/signal_patterns.md) for full detection rules.
### Step 2: Classify & Match to Target Files
Map each signal to the appropriate target:
| Category | Target Files |
|----------|--------------|
| Code Style | `code-reviewer`, `backend-developer`, `frontend-developer` |
| Architecture | `solution-architect`, `api-architect`, `architecture-reviewer` |
| Process | `CLAUDE.md`, orchestrator agents |
| Domain | Domain-specific agents, `CLAUDE.md` |
| Tools | `CLAUDE.md`, relevant specialists |
| New Skill | Create new skill file |
See [data/agent_mappings.md](data/agent_mappings.md) for mapping rules.
### Step 3: Check for Skill-Worthy Signals
Some learnings should become new skills rather than agent updates:
**Skill-Worthy Criteria:**
- Non-obvious debugging (>10 min investigation)
- Misleading error (root cause different from message)
- Workaround discovered through experimentation
- Configuration insight (differs from documented)
- Reusable pattern (helps in similar situations)
**Quality Gates (must pass all):**
- [ ] Reusable: Will help with future tasks
- [ ] Non-trivial: Requires discovery, not just docs
- [ ] Specific: Can describe exact trigger conditions
- [ ] Verified: Solution actually worked
- [ ] No duplication: Doesn't exist already
### Step 4: Generate Proposals
Present findings in structured format:
```markdown
# Reflection Analysis
## Session Context
- **Date**: [timestamp]
- **Messages Analyzed**: [count]
## Signals Detected
| # | Signal | Confidence | Source Quote | Category |
|---|--------|------------|--------------|----------|
| 1 | [learning] | HIGH | "[exact words]" | Code Style |
## Proposed Changes
### Change 1: Update [agent-name]
**Target**: `[file path]`
**Section**: [section name]
**Confidence**: HIGH
```diff
+ New rule from learning
```
## Review Prompt
Apply these changes? (Y/N/modify/1,2,3)
```
### Step 5: Apply with User Approval
**On `Y` (approve):**
1. Apply each change using Edit tool
2. Commit with descriptive message
3. Update metrics
**On `N` (reject):**
1. Discard proposed changes
2. Log rejection for analysis
**On `modify`:**
1. Present each change individually
2. Allow editing before applying
**On selective (e.g., `1,3`):**
1. Apply only specified changes
2. Commit partial updates
## State Management
State is stored in `~/.reflect/` (configurable via `REFLECT_STATE_DIR`):
```yaml
# reflect-state.yaml
auto_reflect: false
last_reflection: "2026-01-26T10:30:00Z"
pending_reviews: []
```
### Metrics Tracking
```yaml
# reflect-metrics.yaml
total_sessions_analyzed: 42
total_signals_detected: 156
total_changes_accepted: 89
acceptance_rate: 78%
confidence_breakdown:
high: 45
medium: 32
low: 12
most_updated_agents:
code-reviewer: 23
backend-developer: 18
skills_created: 5
```
## Safety Guardrails
### Human-in-the-Loop
- NEVER apply changes without explicit user approval
- Always show full diff before applying
- Allow selective application
### Incremental Updates
- ONLY add to existing sections
- NEVER delete or rewrite existing rules
- Preserve original structure
### Conflict Detection
- Check if proposed rule contradicts existing
- Warn user if conflict detected
- Suggest resolution strategy
## Output Locations
**Project-level (versioned with repo):**
- `.claude/reflections/YYYY-MM-DD_HH-MM-SS.md` - Full reflection
- `.claude/skills/{name}/SKILL.md` - New skills
**Global (user-level):**
- `~/.reflect/learnings.yaml` - Learning log
- `~/.reflect/reflect-metrics.yaml` - Aggregate metrics
## Examples
### Example 1: Code Style Correction
**User says**: "Never use `var` in TypeScript, always use `const` or `let`"
**Signal detected**:
- Confidence: HIGH (explicit "never" + "always")
- Category: Code Style
- Target: `frontend-developer.md`
**Proposed change**:
```diff
## Style Guidelines
+ * Use `const` or `let` instead of `var` in TypeScript
```
### Example 2: Process Preference
**User says**: "Always run tests before committing"
**Signal detected**:
- Confidence: HIGH (explicit "always")
- Category: Process
- Target: `CLAUDE.md`
**Proposed change**:
```diff
## Commit Hygiene
+ * Run test suite before creating commits
```
### Example 3: New Skill from Debugging
**Context**: Spent 30 minutes debugging a React hydration mismatch
**Signal detected**:
- Confidence: HIGH (non-trivial debugging)
- Category: New Skill
- Quality gates: All passed
**Proposed skill**: `react-hydration-fix/SKILL.md`
## Troubleshooting
**No signals detected:**
- Session may not have had corrections
- Check if using natural language corrections
**Conflict warning:**
- Review the existing rule cited
- Decide if new rule should override
- Can modify before applying
**Agent file not found:**
- Check agent name spelling
- May need to create agent file first

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{
"ownerId": "kn76g5m73ja7q4gbhrh8h7v0h97zffvw",
"slug": "reflect-learn",
"version": "2.0.0",
"publishedAt": 1769445465505
}

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# Agent Mappings Reference
Maps learning categories to target agent files for updating.
## Agent Directory Structure
```
~/.claude/agents/
├── universal/
│ ├── backend-developer.md
│ ├── frontend-developer.md
│ └── superstar-engineer.md
├── engineering/
│ ├── api-architect.md
│ ├── architecture-reviewer.md
│ ├── code-reviewer.md
│ ├── security-agent.md
│ ├── test-writer-fixer.md
│ └── ...
├── design/
│ └── ui-designer.md
├── orchestrators/
│ ├── tech-lead-orchestrator.md
│ └── ...
└── meta/
└── agentmaker.md
```
## Category to Agent Mapping
### Code Style
| Learning Type | Primary Agent | Secondary Agents |
|--------------|---------------|------------------|
| Naming conventions | `code-reviewer` | `backend-developer`, `frontend-developer` |
| Formatting rules | `code-reviewer` | Project's `.editorconfig` or linter config |
| TypeScript/JavaScript style | `frontend-developer` | `code-reviewer` |
| Python style | `backend-developer` | `code-reviewer` |
| Go style | `backend-developer` | `code-reviewer` |
| Rust style | `backend-developer` | `code-reviewer` |
**Section in Agent File:**
```markdown
## Code Style
## Style Guidelines
## Heuristics > Style
```
### Architecture
| Learning Type | Primary Agent | Secondary Agents |
|--------------|---------------|------------------|
| Design patterns | `solution-architect` | `architecture-reviewer` |
| API design | `api-architect` | `backend-developer` |
| Database patterns | `backend-developer` | `migration` |
| Frontend patterns | `frontend-developer` | `architecture-reviewer` |
| System structure | `solution-architect` | `tech-lead-orchestrator` |
**Section in Agent File:**
```markdown
## Architecture Patterns
## Design Patterns
## Heuristics > Architecture
```
### Process
| Learning Type | Primary Agent | Global Config |
|--------------|---------------|---------------|
| Git workflow | `CLAUDE.md` | Commit hygiene section |
| CI/CD | `devops-automator` | Pipeline config |
| Code review | `code-reviewer` | Review checklist |
| Testing workflow | `test-writer-fixer` | Testing philosophy |
| Deployment | `release-manager` | Release process |
**Section in Agent File:**
```markdown
## Workflow
## Process Guidelines
## Heuristics > Process
```
### Domain
| Learning Type | Primary Target | Notes |
|--------------|----------------|-------|
| Business rules | Project `.claude/agents/` | Domain-specific agent |
| Terminology | `CLAUDE.md` | Glossary section |
| Constraints | Project-specific agent | Validation rules |
| User requirements | `CLAUDE.md` | User preferences section |
**Section in Agent File:**
```markdown
## Domain Rules
## Business Logic
## Terminology
```
### Tools
| Learning Type | Primary Target | Notes |
|--------------|----------------|-------|
| CLI preferences | `CLAUDE.md` | Tool usage section |
| Editor config | `.editorconfig` | Format settings |
| Docker usage | `devops-automator` | Container settings |
| Git settings | `CLAUDE.md` | Commit hygiene |
**Section in Agent File:**
```markdown
## Tool Usage
## CLI Preferences
## Environment Setup
```
### Security
| Learning Type | Primary Agent | Secondary Agents |
|--------------|---------------|------------------|
| Input validation | `security-agent` | `code-reviewer` |
| Authentication | `security-agent` | `api-architect` |
| Authorization | `security-agent` | `backend-developer` |
| Encryption | `security-agent` | `backend-developer` |
| OWASP rules | `security-agent` | `code-reviewer` |
**Section in Agent File:**
```markdown
## Security Heuristics
## Review Heuristics > Security
## Validation Rules
```
## Section Identification
When adding a learning to an agent file, identify the correct section:
### Pattern Matching for Sections
```regex
## Heuristics
## Style
## Guidelines
## Patterns
## Rules
## Best Practices
## Review Checklist
```
### Section Priority
1. Most specific matching section (e.g., "Security" for security rules)
2. Generic "Heuristics" section
3. "Guidelines" or "Rules" section
4. Create new section if none match
### Addition Format
Always add as a bullet point under the appropriate section:
```markdown
## Heuristics
* Existing rule 1
* Existing rule 2
* **New learning from reflection** ← Add here
```
Use bold for newly added rules to distinguish them.
## Conflict Detection
Before adding a new rule, check for conflicts:
### Contradiction Patterns
```regex
# Opposite directives
"never use X" vs "always use X"
"prefer Y" vs "avoid Y"
"use Z" vs "don't use Z"
# Conflicting versions
"use library v1" vs "use library v2"
"Node 18" vs "Node 20"
```
### Resolution Strategy
1. **Newer wins**: If the new learning contradicts an old rule, flag for review
2. **Higher confidence wins**: HIGH > MEDIUM > LOW
3. **More specific wins**: "Never use var in TypeScript" > "Avoid var"
4. **User decision**: When equal, ask user to resolve
## File Paths
### Global Agents (User-level)
```
~/.claude/agents/universal/backend-developer.md
~/.claude/agents/universal/frontend-developer.md
~/.claude/agents/engineering/code-reviewer.md
~/.claude/agents/engineering/api-architect.md
~/.claude/agents/engineering/solution-architect.md
~/.claude/agents/engineering/security-agent.md
~/.claude/agents/engineering/test-writer-fixer.md
~/.claude/agents/design/ui-designer.md
```
### Project Agents (Project-level)
```
.claude/agents/{name}.md
```
### Global Instructions
```
~/.claude/CLAUDE.md
```
### Project Instructions
```
.claude/CLAUDE.md
CLAUDE.md
```
## Skill Creation vs Agent Update
Decide whether to create a new skill or update an agent:
| Criteria | Create Skill | Update Agent |
|----------|--------------|--------------|
| One-off solution to specific error | Yes | No |
| General preference | No | Yes |
| Debugging workaround | Yes | No |
| Code style rule | No | Yes |
| Configuration trick | Yes | Sometimes |
| Process preference | No | Yes |
## Example Mappings
### Example 1: Code Style
**Signal**: "Never use `var` in TypeScript, always use `const` or `let`"
**Confidence**: HIGH
**Category**: Code Style
**Mapping**:
- Primary: `~/.claude/agents/universal/frontend-developer.md`
- Section: `## Style Guidelines`
- Addition: `* Use \`const\` or \`let\` instead of \`var\` in TypeScript`
### Example 2: Architecture
**Signal**: "Prefer cursor-based pagination for APIs"
**Confidence**: MEDIUM
**Category**: Architecture
**Mapping**:
- Primary: `~/.claude/agents/engineering/api-architect.md`
- Section: `## Design Patterns`
- Addition: `* Prefer cursor-based pagination over offset-based for large datasets`
### Example 3: Security
**Signal**: "Always validate inputs on the server, never trust client validation"
**Confidence**: HIGH
**Category**: Security
**Mapping**:
- Primary: `~/.claude/agents/engineering/security-agent.md`
- Section: `## Validation Rules`
- Addition: `* Always validate inputs server-side; client validation is for UX only`
- Secondary: `~/.claude/agents/engineering/code-reviewer.md`
- Section: `## Review Heuristics > Security`
### Example 4: New Skill
**Signal**: "Fixed React hydration mismatch by ensuring server and client render same content"
**Confidence**: HIGH
**Category**: New Skill
**Mapping**:
- Create: `.claude/skills/react-hydration-mismatch-fix/SKILL.md`
- Include: Error message, symptoms, step-by-step fix, verification

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# Signal Detection Patterns
Comprehensive reference for detecting correction signals and learning opportunities in conversations.
## Confidence Levels
### HIGH Confidence (Explicit Corrections)
These patterns indicate the user is explicitly stating a rule or correction. Always apply these learnings.
#### Negative Directives
| Pattern | Type | Example |
|---------|------|---------|
| `never` | correction | "Never use var in TypeScript" |
| `don't` / `do not` | correction | "Don't commit directly to main" |
| `stop doing` | correction | "Stop doing manual deployments" |
| `wrong` | correction | "That's wrong, use snake_case" |
| `not like that` | correction | "Not like that, indent with tabs" |
| `incorrect` | correction | "That's incorrect syntax" |
| `should not` / `shouldn't` | prohibition | "You shouldn't use eval()" |
| `must not` / `mustn't` | prohibition | "Must not expose secrets" |
**Regex Pattern:**
```regex
\b(never|don't|do not|stop doing|wrong|not like that|incorrect|should not|shouldn't|must not|mustn't)\b
```
#### Positive Directives
| Pattern | Type | Example |
|---------|------|---------|
| `always` | requirement | "Always validate inputs" |
| `must` | requirement | "You must use parameterized queries" |
| `required` | requirement | "It's required to have tests" |
| `the rule is` | explicit_rule | "The rule is no console.log in prod" |
| `correct way` | explicit_rule | "The correct way is to use hooks" |
**Regex Pattern:**
```regex
\b(always|must|required|the rule is|correct way)\b
```
#### Frustration Markers
These indicate repeated corrections - highest priority learnings.
| Pattern | Type | Example |
|---------|------|---------|
| `I already told you` | frustration | "I already told you about this" |
| `again?` | frustration | "Wrong again?" |
| `not again` | frustration | "Oh not again" |
| `how many times` | frustration | "How many times do I need to say..." |
**Regex Pattern:**
```regex
(I already told you|again\?|not again|how many times)
```
#### Explicit Rules
| Pattern | Type | Example |
|---------|------|---------|
| `the rule is` | explicit_rule | "The rule is we use ESLint" |
| `you should know` | explicit_rule | "You should know we use Prettier" |
| `remember that` | explicit_rule | "Remember that we're on Node 20" |
| `don't forget` | explicit_rule | "Don't forget the error handling" |
**Regex Pattern:**
```regex
(the rule is|you should know|remember that|don't forget)
```
### MEDIUM Confidence (Approved Approaches)
These patterns indicate the user approved a specific approach. Apply with reasonable confidence.
#### Approval Markers
| Pattern | Type | Example |
|---------|------|---------|
| `perfect` | approval | "Perfect, that's what I wanted" |
| `exactly` | approval | "Exactly right" |
| `that's right` | approval | "That's right, keep it" |
| `yes, like that` | approval | "Yes, like that" |
| `correct` | approval | "Correct implementation" |
**Regex Pattern:**
```regex
\b(perfect|exactly|that's right|yes, like that|correct)\b
```
#### Positive Feedback
| Pattern | Type | Example |
|---------|------|---------|
| `good` | positive_feedback | "Good approach" |
| `great job` | positive_feedback | "Great job on the refactor" |
| `well done` | positive_feedback | "Well done with the tests" |
| `nice` | positive_feedback | "Nice solution" |
| `excellent` | positive_feedback | "Excellent work" |
**Regex Pattern:**
```regex
\b(good|great job|well done|nice|excellent)\b
```
#### Continuation Markers
| Pattern | Type | Example |
|---------|------|---------|
| `keep doing` | continuation | "Keep doing it this way" |
| `continue with` | continuation | "Continue with this approach" |
| `stick with` | continuation | "Stick with React hooks" |
**Regex Pattern:**
```regex
\b(keep doing|continue with|stick with)\b
```
### LOW Confidence (Observations)
These patterns suggest preferences but require validation before encoding as rules.
#### Suggestions
| Pattern | Type | Example |
|---------|------|---------|
| `maybe` | suggestion | "Maybe try TypeScript" |
| `perhaps` | suggestion | "Perhaps use a different library" |
| `might want to` | suggestion | "You might want to add caching" |
| `consider` | suggestion | "Consider using memoization" |
**Regex Pattern:**
```regex
\b(maybe|perhaps|might want to|consider)\b
```
#### Observations
| Pattern | Type | Example |
|---------|------|---------|
| `seems like` | observation | "Seems like this works" |
| `appears to` | observation | "Appears to be faster" |
| `looks like` | observation | "Looks like a good pattern" |
**Regex Pattern:**
```regex
\b(seems like|appears to|looks like)\b
```
## Category Detection
### Code Style
Patterns indicating code style preferences:
```regex
\b(naming|convention|style|format|indent|case|camelCase|snake_case|PascalCase)\b
\b(variable|function|class|method|parameter)\s+name
\b(semicolon|quote|single quote|double quote|tabs|spaces)\b
```
Examples:
- "Use snake_case for Python variables"
- "We prefer single quotes for strings"
- "Indent with 2 spaces, not tabs"
### Architecture
Patterns indicating architectural decisions:
```regex
\b(pattern|architecture|design|structure|module|component|service)\b
\b(separation|coupling|cohesion|dependency|layer|abstraction)\b
\b(microservice|monolith|serverless|event-driven)\b
```
Examples:
- "Use dependency injection for services"
- "Keep components loosely coupled"
- "Follow the repository pattern"
### Process
Patterns indicating workflow preferences:
```regex
\b(workflow|process|step|procedure|protocol|practice)\b
\b(commit|branch|merge|review|deploy|test|ci|cd)\b
\b(pr|pull request|code review|approval)\b
```
Examples:
- "Always run tests before commit"
- "Use conventional commits"
- "Squash commits on merge"
### Domain
Patterns indicating business logic:
```regex
\b(business|domain|logic|rule|requirement|constraint)\b
\b(customer|user|client|account|order|payment|invoice)\b
\b(validate|verify|check|ensure|confirm)\b
```
Examples:
- "Orders must be validated before processing"
- "Users need email verification"
- "Payments require two-factor auth"
### Tools
Patterns indicating tool preferences:
```regex
\b(tool|cli|command|terminal|shell|editor|ide)\b
\b(git|npm|yarn|pnpm|docker|kubernetes)\b
\b(config|setting|environment|variable|env)\b
```
Examples:
- "Use pnpm instead of npm"
- "Configure ESLint with these rules"
- "Run Docker in production"
### New Skill
Patterns indicating skill-worthy discoveries:
```regex
\b(workaround|trick|hack|solution|fix|debug|resolve)\b
\b(error|bug|issue|problem)\s+(was|is|fixed|solved|resolved)\b
(took|spent)\s+\d+\s*(min|minute|hour|day)
\b(finally|after trying|turns out|the issue was)\b
```
Examples:
- "The workaround is to clear the cache first"
- "After 2 hours debugging, found the issue was..."
- "Turns out the error message was misleading"
## Edge Cases
### False Positives to Avoid
Some patterns may match but don't indicate learnings:
- Rhetorical questions: "Why would you never do X?" (not a directive)
- Hypotheticals: "If you never use Y, then..." (conditional)
- Quotes/references: "The docs say never..." (not user's directive)
- Negations: "It's not wrong to..." (opposite meaning)
### Context Sensitivity
Consider surrounding context:
- "That's not wrong" - NOT a correction
- "That's not right" - IS a correction
- "Never mind" - NOT a directive about future behavior
- "Always" in a loop - NOT a behavioral directive
## Combining Patterns
When multiple patterns match:
1. Use the highest confidence pattern
2. If equal confidence, use the most specific category
3. Prefer explicit rules over implied preferences
4. Prioritize frustration markers (indicate repeated issue)
## Implementation Notes
The `signal_detector.py` script implements these patterns. To update patterns:
1. Add pattern to appropriate `*_PATTERNS` list
2. Run `python signal_detector.py --test` to verify
3. Add test case for new pattern
4. Update this documentation

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{
"name": "Reflect - Agent Self-Improvement",
"emoji": "🪞",
"description": "Self-improvement through conversation analysis. Extracts learnings from corrections, success patterns, and session outcomes. Encodes learnings permanently into agent definitions for continuous improvement across all future sessions.",
"category": "meta",
"author": "Claude Code Toolkit",
"version": "2.0.0",
"readme": "README.md",
"tags": [
"reflection",
"self-improvement",
"learning",
"meta",
"agent-development",
"continuous-improvement"
],
"features": [
"Signal detection with confidence levels (HIGH/MEDIUM/LOW)",
"Automatic category classification (Code Style, Architecture, Process, Domain, Tools)",
"Agent file updates with version control",
"New skill generation from debugging discoveries",
"Metrics tracking and improvement statistics",
"Human-in-the-loop approval workflow"
],
"repository": "https://github.com/stevengonsalvez/ai-coder-rules",
"license": "MIT",
"keywords": [
"reflect",
"self-improvement",
"learning",
"agent",
"corrections",
"patterns",
"meta-cognition"
],
"defaults": {
"state_dir": "~/.reflect",
"auto_reflect": false,
"confidence_threshold": "medium"
},
"clawdbot": {
"triggers": [
"reflect",
"self-reflect",
"review session",
"extract learnings"
]
}
}