immacualate/claude-forge/skill-factory
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Checking that the SKILL.md file is still in the repository.
Analyze session work and automatically convert reusable patterns into Claude Code skills. Use when: "세션을 스킬로", "스킬 만들어", "이거 스킬로", "skill factory", "이 작업 자동화해", "스킬 추출", "make this a skill", "extract skill", "convert to skill", "스킬 팩토리", "자동 스킬 생성". Differs from skill-creator (archived) and manage-skills (drift detection): this skill actively analyzes sessions, checks for duplicates, and creates skills via Agent Teams.
Install
npx vskill@latest install immacualate/claude-forge/skill-factorySKILL.md
Skill Factory
Automated pipeline: session analysis -> duplicate check -> skill creation. Requires: Python 3.8+, bash, git. Agent Teams path requires CLAUDE_CODE_EXPERIMENTAL_AGENT_TEAMS=1.
| Existing Skill | Role | skill-factory Difference | |
|---|---|---|---|
| skill-creator (archived) | Manual 6-step guide | Automated pipeline | |
| manage-skills | Drift detection (verify-* skills) | Proactive skill generation (manage-skills verifies existing; skill-factory creates new) | |
| continuous-learning | Passive pattern extraction | On-demand + team execution |
Parameter Parsing
Parse $ARGUMENTS for flags:
| Flag | Default | Description | |
|---|---|---|---|
--dry-run | false | Analyze and report only, no file creation | |
--no-team | false | Run sequentially without Agent Teams | |
--target | (auto) | Specific pattern name to extract | |
--scope | global | global (~/. claude/skills/) or project (.claude/skills/) |
If no arguments, run full auto-detection pipeline.
Phase 1: Session Analysis
Collect what happened in this session:
From collected changes, identify candidate patterns - repeatable workflows that appeared:
- Multi-step sequences - 3+ actions performed in consistent order
- Tool combinations - Specific tools used together (e.g., Grep + Read + Edit)
- Domain procedures - File types or directories accessed with specific operations
- Repeated transformations - Same type of change applied to multiple files
If --target is specified, focus analysis on that named pattern only.
For each candidate, produce a JSON entry (internal, not shown to user):
Present findings to user:
Wait for user selection before proceeding.
Phase 2: Similarity Check
For each selected pattern, check against existing inventory.
Step 1: Scan inventory
Step 2: Score similarity
Step 3: Apply decision logic (see references/decision-tree.md)
Present results to user:
Wait for user decision per pattern.
Phase 3: Blueprint
For each CREATE/UPDATE/MERGE decision, design the skill structure.
CREATE Blueprint
Select template type from references/skill-templates.md:
- Workflow for sequential processes
- Task/Tool for operation collections
- Reference for domain knowledge
- Verification for automated checks
Generate blueprint:
Wait for user approval.
UPDATE Blueprint
For UPDATE verdicts (score 0.3-0.6), plan a lightweight addition to the existing skill:
MERGE Blueprint
For MERGE verdicts (score 0.6-0.8), plan a significant extension of the existing skill:
Phase 4: Execution
Two paths based on --no-team flag and Agent Teams availability.
Check Agent Teams availability:
If --no-team is set or env var is missing/0, use Path B automatically.
Path A: Agent Teams (default)
Read references/team-composition.md for full team details.
Team: 3 teammates (tami, jiwon, duri)
Pipeline:
- tami completes analysis -> reports to lead
- Lead confirms with user (Checkpoint 1-2)
- jiwon creates skill files -> reports to lead
- Lead confirms with user (Checkpoint 3)
- duri validates and registers -> reports to lead
- Lead confirms with user (Checkpoint 4)
- Shutdown all teammates, TeamDelete
Path B: Sequential (--no-team)
Execute the same phases inline without Agent Teams:
- Run
scan-inventory.shandsimilarity-scorer.pydirectly - Checkpoint 1-2: Present similarity results, ask user for CREATE/UPDATE/MERGE/SKIP per pattern
- Design blueprint based on template selection
- Checkpoint 3: Present blueprint, wait for user approval
- Create/update skill directory and files based on approved blueprint
- Run
validate-skill.shto verify - Checkpoint 4: Present validation results, ask user to register or edit
- Register and log
--dry-run Mode
Stop after Phase 3 (blueprint). Print the blueprint and exit without creating files:
Phase 5: Registration
After validation passes:
- Log creation - Append to
~/.claude/skill-factory.log:
`` [2026-02-18T14:30:00] CREATED api-load-test (global) from session patterns [2026-02-18T14:30:00] MERGED batch-operations into nano-pdf ``
- Scope placement:
--scope global:~/.claude/skills/<name>/--scope project:.claude/skills/<name>/
- Optional CLAUDE.md update: If project-scoped, offer to add skill reference to project CLAUDE.md.
Output Format
Final report after all patterns are processed:
Error Handling
| Situation | Action | |
|---|---|---|
| No git history | Analyze only staged/unstaged changes | |
| No patterns found | "No reusable patterns detected. Try after a more complex session." | |
| scan-inventory.sh fails | Fall back to manual inventory (glob SKILL.md files) | |
| similarity-scorer.py fails | Skip similarity check, default to CREATE | |
| Agent Teams unavailable | Auto-fallback to --no-team mode | |
| validate-skill.sh fails | Show errors, let user fix or cancel | |
| User cancels at checkpoint | Abort gracefully, no partial files left |
Related Files
| File | Purpose | When to Read | |
|---|---|---|---|
| scripts/scan-inventory.sh | Scan all skills/commands/agents to JSON | Phase 2 - always | |
| scripts/similarity-scorer.py | 4-dim similarity scoring | Phase 2 - per pattern | |
| scripts/validate-skill.sh | Validate created skill structure | Phase 5 - after creation | |
| references/decision-tree.md | CREATE/UPDATE/MERGE/SKIP logic | Phase 2 - for decisions | |
| references/team-composition.md | tami/jiwon/duri team setup | Phase 4 - Agent Teams path | |
| references/skill-templates.md | Skill type templates | Phase 3 - blueprint design |
Security
- Security scanPassed, 100 of 100Pattern checks on the skill's files.
- Model reviewNot runA model review is scheduled for the next rescan.
Quality evaluation
- Task evaluationNot runNo evaluation yet. Run one in Skill Studio.
Source
- SKILL.md in the repositoryCheckingskills/skill-factory/SKILL.md
Popularity
- Repository stars
- 5
- 7-day trend score
- 9
Stars and forks are for the whole GitHub repository, not this skill alone. Not refreshed yet.
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