jikime-workflow-learning
Continuous learning system - extract, store, and reuse patterns from Claude Code sessions
Best use case
jikime-workflow-learning is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Continuous learning system - extract, store, and reuse patterns from Claude Code sessions
Teams using jikime-workflow-learning 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/jikime-workflow-learning/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How jikime-workflow-learning Compares
| Feature / Agent | jikime-workflow-learning | 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?
Continuous learning system - extract, store, and reuse patterns from Claude Code sessions
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
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SKILL.md Source
# Continuous Learning Skill
Automatically extract reusable patterns from Claude Code sessions and store them for future use.
## Philosophy
```
Every session is a learning opportunity:
├─ Error resolutions → Future prevention
├─ User corrections → Preference learning
├─ Workarounds → Knowledge base
├─ Debugging techniques → Reusable strategies
└─ Project-specific patterns → Team knowledge
```
---
## How It Works
### Session Lifecycle
```
Session Start
↓
Load relevant learnings from .jikime/learnings/
↓
Development work...
↓
Session End (Stop hook)
↓
Analyze session for patterns
↓
Extract learnings with confidence scoring
↓
Store in .jikime/learnings/
↓
Next Session: Patterns available
```
### Automatic Extraction
At session end, the system analyzes:
- Error messages and resolutions
- User corrections to Claude's suggestions
- Workarounds for framework/library quirks
- Debugging techniques that worked
- Project-specific conventions
---
## Pattern Categories
For detailed YAML examples and patterns, see:
- [Pattern Categories](modules/pattern-categories.md) - Error resolution, user corrections, workarounds, debugging, conventions
| Category | Description | Typical Confidence |
|----------|-------------|-------------------|
| `error_resolution` | How specific errors were resolved | 0.80-0.95 |
| `user_correction` | User corrections to Claude's output | 0.85-0.92 |
| `workaround` | Framework/library quirks solutions | 0.90-0.98 |
| `debugging` | Effective debugging approaches | 0.75-0.90 |
| `project_convention` | Project-specific patterns | 0.85-0.95 |
---
## Storage Structure
```
.jikime/
├── learnings/
│ ├── index.json # Searchable index
│ ├── errors/
│ │ ├── typescript.yaml
│ │ ├── react.yaml
│ │ └── nextjs.yaml
│ ├── corrections/
│ │ └── style-preferences.yaml
│ ├── workarounds/
│ │ ├── nextjs-14.yaml
│ │ └── prisma.yaml
│ ├── debugging/
│ │ └── react-state.yaml
│ ├── conventions/
│ │ ├── api-patterns.yaml
│ │ └── file-structure.yaml
│ └── sessions/
│ ├── 2024-01-22-summary.md
│ └── 2024-01-21-summary.md
```
### Index Structure
```json
{
"version": "1.0.0",
"last_updated": "2024-01-22T15:30:00Z",
"total_patterns": 47,
"categories": {
"error_resolution": 15,
"user_correction": 8,
"workaround": 12,
"debugging": 7,
"project_convention": 5
},
"top_patterns": [
{"id": "err-ts-001", "confidence": 0.95, "frequency": 12},
{"id": "wk-nextjs-003", "confidence": 0.93, "frequency": 8}
],
"technologies": ["typescript", "react", "nextjs", "prisma"]
}
```
---
## Confidence Scoring
Patterns are scored for reliability:
```
Confidence = (
base_score * 0.4 +
frequency_score * 0.3 +
recency_score * 0.2 +
source_reliability * 0.1
)
Base Score:
- Official docs: 1.0
- User correction: 0.9
- Successful resolution: 0.8
- Experimental: 0.6
Frequency Score:
- Used 10+ times: 1.0
- Used 5-9 times: 0.8
- Used 2-4 times: 0.6
- Used once: 0.4
Recency Score:
- Used this week: 1.0
- Used this month: 0.8
- Used this quarter: 0.6
- Older: 0.4
```
### Confidence Thresholds
| Level | Score | Treatment |
|-------|-------|-----------|
| High | 0.85+ | Apply automatically |
| Medium | 0.65-0.84 | Suggest with context |
| Low | 0.40-0.64 | Available for search |
| Experimental | <0.40 | Flag for review |
---
## Orchestrator Integration
### J.A.R.V.I.S. (Development)
```
Session Start:
→ Load high-confidence patterns for active technologies
→ Summarize: "Loaded 12 patterns for React/TypeScript"
During Development:
→ Apply patterns proactively
→ "Based on learned pattern: using optional chaining here"
Session End:
→ Extract new patterns
→ Report: "3 new patterns learned this session"
Predictive Suggestions:
→ "Based on past sessions, you might also want to..."
```
### F.R.I.D.A.Y. (Migration)
```
Migration Start:
→ Load patterns for source/target frameworks
→ "Loaded 8 migration patterns for Vue → React"
During Migration:
→ Apply migration-specific workarounds
→ Track framework-specific quirks
Migration End:
→ Store migration patterns for future use
→ Export as reusable migration guide
```
---
## Session Summary
At session end, generate a summary:
```markdown
# Session Summary: 2024-01-22
## Duration
Started: 10:30 AM
Ended: 2:15 PM (3h 45m)
## Work Completed
- Implemented user authentication
- Fixed 3 TypeScript errors
- Resolved hydration mismatch issue
## Patterns Learned
### New Patterns (3)
1. **Error Resolution**: TypeScript strict null checks
- Confidence: 0.85
- Category: error_resolution
2. **Workaround**: Next.js 14 cache invalidation
- Confidence: 0.78
- Category: workaround
3. **Convention**: API response structure
- Confidence: 0.92
- Category: project_convention
### Reinforced Patterns (2)
- React useState with objects (frequency: 5 → 6)
- Prisma relation queries (frequency: 3 → 4)
## For Next Session
- Continue with payment integration
- Review auth edge cases
- Consider adding rate limiting
```
---
## Export/Import
For detailed CLI commands and export format, see:
- [CLI Commands](modules/cli-commands.md) - Export, import, and search commands
Quick reference:
```bash
# Export patterns
jikime-adk learnings export --output learnings-export.yaml
# Import from another project
jikime-adk learnings import --source patterns.yaml --strategy merge
```
---
## Hook Integration
### Session End Hook
```json
{
"hooks": {
"Stop": [
{
"matcher": "*",
"hooks": [
{
"type": "command",
"command": "jikime-adk hooks learning-extract"
}
]
}
]
}
}
```
### Session Start Hook
```json
{
"hooks": {
"SessionStart": [
{
"matcher": "*",
"hooks": [
{
"type": "command",
"command": "jikime-adk hooks learning-load"
}
]
}
]
}
}
```
---
## Configuration
```yaml
# .jikime/config/learning.yaml
learning:
enabled: true
# Extraction settings
extraction:
min_session_length: 10 # Minimum messages to analyze
auto_extract: true # Extract on session end
require_confirmation: false # Ask before saving patterns
# Pattern settings
patterns:
min_confidence: 0.40 # Minimum to store
auto_apply_threshold: 0.85 # Apply without asking
max_age_days: 365 # Archive old patterns
# Categories to track
categories:
- error_resolution
- user_correction
- workaround
- debugging
- project_convention
# Ignore patterns
ignore:
- simple_typos
- one_time_fixes
- external_api_issues
- environment_specific
```
---
## Searching Patterns
Query stored patterns (see [CLI Commands](modules/cli-commands.md) for full examples):
```bash
# Search by keyword
jikime-adk learnings search "useState"
# Search by category
jikime-adk learnings search --category workaround
# Search by technology
jikime-adk learnings search --tech nextjs
```
---
## Privacy & Security
### Sensitive Data Handling
```yaml
# Patterns never stored:
- API keys, tokens, secrets
- Passwords or credentials
- Personal information
- Environment-specific values
# Before storage:
- Redact secrets: sk-*** → [REDACTED]
- Generalize specific values
- Remove project-specific paths
```
### Local Storage Only
```
All learnings stored locally in .jikime/learnings/
- Not synced to cloud by default
- Export explicitly for sharing
- Add to .gitignore if sensitive
```
---
## Best Practices
### DO
1. **Review high-frequency patterns** - They shape future behavior
2. **Adjust confidence when wrong** - Learning improves over time
3. **Export valuable patterns** - Share across projects
4. **Clean stale patterns** - Remove outdated learnings
5. **Categorize correctly** - Aids future retrieval
### DON'T
1. **Trust low-confidence blindly** - Verify before applying
2. **Store one-time fixes** - Not reusable
3. **Keep outdated patterns** - Technology evolves
4. **Ignore user corrections** - They signal preferences
5. **Over-generalize** - Some patterns are context-specific
---
## Works Well With
- `jikime-foundation-core`: Core workflow integration
- `jikime-workflow-spec`: SPEC-based development
- `jikime-workflow-eval`: Evaluation framework
- `jikime-workflow-project`: Project initialization
- `jikime-foundation-claude`: Claude Code patterns
---
Last Updated: 2026-01-25
Version: 1.0.0
Integration: SessionEnd hook, J.A.R.V.I.S./F.R.I.D.A.Y., Export/ImportRelated Skills
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