Commands
This skill captures a successful custom security testing approach and guides the user through saving it as a reusable specialist skill, including defining priorities, focus areas, and techniques.
How to Install
git clone --depth 1 https://github.com/gadievron/raptor.git && cp raptor/.claude/commands ~/.claude/skills/create-skill.md -r/create-skill - Save Custom Approach as Reusable Skill
Save a successful custom approach as a reusable specialist skill.
When to Use
After you've helped the user with a custom security testing approach: - Custom analysis focus (e.g., "focus on API security only") - Custom priority order (e.g., "check auth before secrets") - Custom techniques (e.g., "specific testing methodology") - Successful findings (approach actually worked)
What This Does
Guides skill creation process:
Step 1: Capture Successful Approach
What was successful about this approach?
Examples:
- Custom priorities: Auth → API security → Business logic
- Specific focus: API endpoint authentication testing
- Custom technique: Token generation + endpoint fuzzing
- Domain expertise: Mobile app security patterns
Step 2: Define Skill Parameters
Skill name: [descriptive_name]
Trigger keywords: [when should this auto-load?]
Domain: [what type of targets?]
Examples:
- Name: api_security_auth_focus
- Keywords: API, REST, authentication, admin panel
- Domain: Web APIs with authentication
Step 3: Extract Reusable Patterns
Review approach for: - ✓ Generalizable patterns (not hardcoded to one target) - ✓ Reusable priorities (applicable to similar targets) - ✓ Tool combinations (what worked together) - ✗ Target-specific details (remove these)
Step 4: Validate Token Budget
Skill size: ___ tokens (must be <500 tokens)
Current total skills: ___ (warn if >10 skills)
Session impact: +___ tokens when auto-loaded
Step 5: Create Skill File
Save to: .claude/skills/[skill_name]/SKILL.md (the
canonical Claude Code skills directory). For
single-file skills, .claude/skills/[skill_name].md
also works — Claude Code's skill discovery walks
.claude/skills/ and picks up both layouts.
(Pre-fix this said tiers/specialists/custom/[name].md.
That path is from an earlier RAPTOR layout that
predates Claude Code's skills mechanism — files there
aren't auto-loaded by Claude Code today, so saving
new skills there would have made them invisible to
the LLM. Existing files under tiers/personas/ and
tiers/specialists/ are still loaded VIA EXPLICIT
prompts, but new skills should go under
.claude/skills/ for auto-load.)
Skill structure:
# [Skill Name]
# Created: [date]
# Source: Successful approach from [session]
# Token cost: [X] tokens
# Auto-loads: [trigger keywords]
## Core Philosophy
[What makes this approach unique/successful]
## When to Use
[What types of targets/situations]
## Approach
[Successful priorities, techniques, tools]
## Integration with Python
[How this guides Python execution parameters]
Step 6: Test Auto-Loading
Verify skill will auto-load correctly: - Keywords defined clearly - File in correct location - Token budget acceptable
Token Budget Guidelines
Skill size limits: - Minimum: 200 tokens (enough for useful content) - Recommended: 300-400 tokens (sweet spot) - Maximum: 500 tokens (hard limit, enforced)
Total skills warning: - Yellow (5 skills): 1,500-2,000 tokens in skills - Red (10 skills): 3,000-4,000 tokens (approaching budget) - Critical (15+ skills): Consider consolidating or removing unused
Example Skill Creation
User: /create-skill
Claude: What successful approach should we save?
User: "We focused on API authentication, checking auth bypass before anything else, and it found critical issues faster"
Claude:
✓ Extracting approach patterns...
Skill preview:
- Name: api_auth_priority
- Keywords: API, REST, authentication, auth bypass
- Focus: Authentication issues in web APIs
- Priority: Auth bypass → API security → Input validation
- Size: 380 tokens ✓
Create this skill? [Y/n/Customize]
User: Y
Claude: ✓ Created: .claude/skills/api_auth_priority/SKILL.md
Will auto-load when keywords match: API, authentication
Test it now? Run /scan on API codebase
Quality Checks
Before saving skill: - [ ] Not overfitted to one target (generalized patterns) - [ ] Token limit respected (<500 tokens) - [ ] Keywords defined (will auto-load correctly) - [ ] Approach documented (clear priorities/techniques) - [ ] Integration clear (how it guides Python parameters)
Maintenance
Skills are stored in: .claude/skills/
Manage skills:
- List: ls .claude/skills/
- Disable: Add .disabled suffix to the skill directory or file
- Remove: Delete the skill directory (or the bare .md file)
- Edit: Modify the skill's SKILL.md (or single-file .md) directly
(Pre-fix this section pointed at tiers/specialists/custom/ —
an earlier RAPTOR layout that predates Claude Code's skills
mechanism. Files there aren't auto-loaded today, so saving
new skills there made them invisible to the LLM.)
Quarterly review prompt (if 5+ skills exist):
Review custom skills? Usage stats available.
Details
| Category | AI/ML → ml |
| Source | gadievron/raptor |
| SKILL.md | View on GitHub → |
| Repo Stars | ★ 3.0K |
| Est. per Skill | 234 (shared across 13 skills from this repo) |
| Difficulty | Intermediate |
| Risk Level | N/A |
Related Skills
Works Well With
Skills from the same repository — often designed to work together