Automated summary
A step-by-step workflow that turns a security testing approach that worked into a reusable skill, complete with name, trigger keywords and a token budget.
Strengths
- Six explicit steps, from capturing the successful approach to verifying that auto-loading works.
- Explicitly directs output to .claude/skills/ and corrects an older path that would have left new skills invisible to Claude Code.
- Gives concrete size guidance for skills (200-500 tokens) and warning thresholds for the total skill count.
- Pushes for generalization: strip target-specific details and keep only patterns that transfer to similar targets.
Limitations
- The 500-token ceiling is advisory only; nothing mechanically prevents an oversized skill file.
- Does not check for duplicates or overlap with skills already in the catalog.
- Relies on the user's judgement about what is genuinely reusable, with no technical validation of the approach itself.
Use it right after a security testing session where a particular prioritization or technique paid off and is worth replaying on future targets.
Skip it for one-off findings tied to a single target, or when you want to author a skill outside the security testing context.
Security analysis
SafeThe skill only provides guidance for creating and saving reusable skill files. It does not instruct any destructive, exfiltrating, or obfuscated actions, and it declares no allowed tools. Writing files to the user's own .claude/skills directory is a legitimate, low-risk operation.
No concerns found
How this analysis is madeExamples
/create-skill — save the approach we just used: checking authentication bypass before secrets scanning on web APIs. It found the critical issues much faster./create-skill. Turn our token generation + endpoint fuzzing routine for mobile backends into a skill called mobile_api_recon, triggered by keywords mobile, API, JWT./create-skill — I want to keep this priority order as a reusable skill: auth bypass, then API security, then business logic. Name it api_auth_priority.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
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
.disabledsuffix to the skill directory or file - Remove: Delete the skill directory (or the bare
.mdfile) - 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.
From the file to a first result
The download contains exactly the content displayed on this page. This copy may differ from the latest version in the source repository.
View the source and supporting filesThis download contains SKILL.md only. Any scripts, references, templates and dependencies are not included. Get the required files from the source, preserving their directory structure, before continuing.
1. Download the file
Download SKILL.mdFrom the root of a test project, save the file as .skill-downloads/save-custom-approach-as-reusable-skill-mttmx7b7/SKILL.md, or use the command below. This folder is for inspecting the skill before installation.
Command for macOS/Linux or WSL: requires a POSIX shell and curl. On Windows without WSL, use the download button and create the folder manually.
mkdir -p '.skill-downloads/save-custom-approach-as-reusable-skill-mttmx7b7' && curl --fail --show-error --location 'https://skills-guides.com/api/skills/save-custom-approach-as-reusable-skill-mttmx7b7/download' --output '.skill-downloads/save-custom-approach-as-reusable-skill-mttmx7b7/SKILL.md.part' && mv '.skill-downloads/save-custom-approach-as-reusable-skill-mttmx7b7/SKILL.md.part' '.skill-downloads/save-custom-approach-as-reusable-skill-mttmx7b7/SKILL.md'2. Check prerequisites
Read SKILL.md before using it. If it references scripts or external services, inspect them and prepare the required access in your test environment.
No recognized prerequisites section in this file. This does not mean it is self-contained: libraries, tools and access requirements may be mentioned elsewhere in the content or source repository.
The platforms on this page are catalog indications. The paths below follow tool documentation; they do not prove this skill has been run in those tools. No minimum tool version is confirmed for this listing.
3. Load the skill
This file does not provide a usable name/description header for this native procedure. It remains available to download and inspect; use the manual method below.
Manual method or another tool: attach SKILL.md to a conversation, or open it in an agent that can read files. Include any required supporting resources. No universal folder is recognized by every tool.
4. Try a first task
Use a short, synthetic input: an API endpoint, a small document or an interface brief. In a new conversation, attach the file or give the agent its path, then adapt this request:
Read .skill-downloads/save-custom-approach-as-reusable-skill-mttmx7b7/SKILL.md and apply its instructions to this example: [describe a test input]. Identify any missing files, dependencies or access. Produce the result requested by the skill without inventing data or running unreviewed scripts.Expected result: output matching the skill instructions, or a precise list of missing prerequisites. A read confirmation alone does not validate a first use. If an external resource is unavailable, that path remains untested.
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