Create a Reusable Security Skill

VerifiedSafe

Guide for turning a successful security testing approach into a reusable skill, covering pattern capture, token budget checks, and validation.

Sby Skills Guide Bot
ProductivityIntermediate
3010/18/2026
Claude Code
#skill-authoring#meta-skill#knowledge-capture#token-budget#security-testing

Recommended for

Our review

Turns a successful ad-hoc approach from a session into a reusable SKILL.md file saved under .claude/skills/, with a token-budget check and auto-load verification.

Strengths

  • Six-step workflow from capturing the successful approach through testing auto-loading
  • Enforces a 200–500 token budget per skill and warns as the total skill count grows
  • Explicitly instructs stripping target-specific details so only generalizable patterns remain
  • Requires operator confirmation before writing and points to the current canonical path instead of the legacy RAPTOR location

Limitations

  • Token limits are advisory and not mechanically enforced
  • The skill-discovery and auto-loading behavior described is specific to Claude Code
  • The confirmation preview is LLM-authored from session content, which may include target-derived text
When to use it

Use it when a session has produced a custom security-testing approach (analysis focus, priority order, or technique) that worked and should be reused.

When not to use it

Avoid it for one-off findings tied to a single target, or when the approach has not yet been validated as successful.

Security analysis

Safe
Quality score78/100

The skill is a meta-workflow for capturing and saving reusable custom security-testing approaches as skill files. It does not execute destructive commands, exfiltrate data, or bypass safety controls. File operations are limited to writing and managing skill definitions under the user's own .claude/skills directory, with explicit confirmation before creation.

No concerns found

Examples

Save a priority order
/create-skill — we found that checking API auth bypass before secrets scanning caught critical issues fastest. Save that priority order as a reusable skill.
Codify a technique
Turn this mobile app security technique — token generation plus endpoint fuzzing — into a skill that auto-loads for mobile targets.
Persist a custom focus
Save our custom analysis focus, 'API security only', as an auto-loading skill for REST targets and check the token budget before writing it.

description: Save a custom approach as a reusable skill dispatch: skill

/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

Confirm before writing. Show the skill preview and take the operator's confirmation (Create this skill? [Y/n/Customize], as in the example below). The preview is LLM-authored from session content — in a scan session that carries target-derived text — so render it with non-printables escaped and bound long excerpts with an explicit elision marker (CLAUDE.md § INTERACTIVE PROMPTS display integrity).

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/ are still loaded via explicit prompts and via the Python methodology loader, 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 — keep to it; not mechanically 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.
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