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Agent skill

Skillkit

by rfxlamia in rfxlamia/skillkit

Toolkit for creating and validating skills and subagents. An agent skill from rfxlamia/skillkit.

Apache-2.0Auto-check passedAgent Workflows

Install Skillkit

skills CLI
$ npx skills add rfxlamia/skillkit --skill skillkit -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install rfxlamia/skillkit skillkit --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/rfxlamia/skillkit.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/skillkit .claude/skills/skillkit && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
skillkit
GitHub stars
102
Token cost
~3.7k tokens
SKILL.md length
1,466 words
Files
72 (incl. scripts, references)
Skills in repo
2
Repo updated
First seen
Licence
Apache-2.0

At a glance

Toolkit for creating and validating skills and subagents. An agent skill from rfxlamia/skillkit.

  • Works in 3 steps: Explicit flag: --mode fast or --mode full → Skill marker: .skillkit-mode file content → If unknown: stop and ask user to choose…
  • : creating a new skill (fast
  • SKILL.md covers Section 1: Intent Detection &…, Section 2: Creation Workflows…, Section 3: Validation Workflow… and Section 4: Decision Workflow…, plus 7 more sections
  • Calls python

What it does

Skillkit is an agent skill from rfxlamia/skillkit. Toolkit for creating and validating skills and subagents. Use when: creating a new skill (fast or full mode), validating an existing skill, deciding Skills vs Subagents, migrating docs to skills, estimating token cost, or running a security scan. Triggers: "create skill", "build skill", "validate skill", "new subagent", "skills vs subagents", "estimate tokens", "security scan".

Its SKILL.md is about 3.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 76 other files, including scripts and reference files (for example `.claude-plugin/plugin.json`, `commands/skillkit.md` and `commands/validate-plan.md`).

It sits in Agent Workflows, covering Subagents, Security review and LLM cost and token optimization. The repository describes itself as: An open toolkit for creating reusable skills that extend how your AI agent works. The licence is Apache-2.0.

When your agent uses it

  • : creating a new skill (fast
  • Validating an existing skill
  • Deciding Skills vs Subagents
  • Migrating docs to skills

Example prompts

  • “create skill”
  • “build skill”
  • “validate skill”
  • “/skillkit”

Requirements

  • Python 3

Workflow steps

3 steps, taken from the first numbered list in SKILL.md.

  1. Explicit flag: --mode fast or --mode full
  2. Skill marker: .skillkit-mode file content
  3. If unknown: stop and ask user to choose fast or full

What it can do on your machine

Read from SKILL.md and the folder at commit 5021813. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Skillkit loads about 3.7k tokens when it runs, and up to ~30k if it reads all its reference files. Until then it costs about 97 tokens; SKILL.md has 1,466 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~97
When it runs · the whole SKILL.md, loaded when a task matches
~3.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~30k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from rfxlamia/skillkit at commit 5021813, republished under its Apache-2.0 licence (© rfxlamia). 1,466 words, ~3,678 tokens.

Download SKILL.mdSave it as .claude/skills/skillkit/SKILL.md (or your agent's skills folder). This skill also uses 71 other files; get the full folder from GitHub.
name
skillkit
description
Toolkit for creating and validating skills and subagents. Use when: creating a new skill (fast or full mode), validating an existing skill, deciding Skills vs Subagents, migrating docs to skills, estimating token cost, or running a security scan. Triggers: "create skill", "build skill", "validate skill", "new subagent", "skills vs subagents", "estimate tokens", "security scan".
category
core

Section 1: Intent Detection & Routing

Detect user intent, route to appropriate workflow.

IntentKeywordsRoute To
Full skill creation"create skill", "build skill", "new skill"Section 2
Subagent creation"create subagent", "build subagent", "new subagent"Section 6
Validation"validate", "check quality"Section 3
Decision"Skills vs Subagents", "decide", "which to use"Section 4
Migration"convert", "migrate doc"Section 5
Single tool"validate only", "estimate tokens", "scan"Section 7

PROCEED to corresponding section after intent detection.

Stop Condition (Mandatory):

  • If multiple routes match or intent is ambiguous: stop, ask user to choose one route.
  • Do not proceed until user confirms the route.

Workflow Value: Research-driven approach validates design before building. Sequential steps with checkpoints produce 9.0/10+ quality vs ad-hoc creation.

Section 2: Creation Workflows (Dual Mode)

Prerequisites: Skill description provided, workspace available.

Mode Selection (Required at Start)

Detect or prompt for workflow mode before running the creation flow.

Stop Condition (Mandatory):

  • If mode is not explicitly provided: stop and ask "Do you want fast or full mode?"
  • Do not continue until user confirms the mode.
ModeStepsValidationQuality TargetTime
fast10Structural only>=9.0/10<10 min
full14Structural + Behavioral>=9.0/10 and behavioral >=7.0<20 min

No implicit default mode is allowed when mode is not explicitly known.

Workflow A: Fast Mode (10 Steps)

Use when .skillkit-mode contains fast or marker does not exist.

→ READ references/section-2-fast-creation-workflow.md IN FULL before starting. Create a task for each step listed in that file, then follow them in order. The outline below is a summary only — the reference file is authoritative.

Phase 1: Decision & Research

  • Step 0: Decide approach (decision_helper.py)
  • Step 1: Research and proposals
  • Step 2: User validation
  • Stop Condition: Stop and request user approval before continuing to Step 3.

Phase 2: Creation

  • Step 3: Initialize skill (init.py skill <name> --mode fast)
  • Step 4: Create content

Phase 3: Structural Validation

  • Step 5: Validate skill (validate_skill.py) — runs structure + security + tokens in one call

Phase 4: Packaging

  • Step 6: Progressive disclosure check
  • Step 7: Generate tests (test_generator.py)
  • Step 8: Quality assessment (quality_scorer.py)
  • Step 9: Package (package_skill.py)
Workflow B: Full Mode (14 Steps)

Use when .skillkit-mode contains full.

→ READ references/section-2-full-creation-workflow.md IN FULL before starting. Create a task for each step listed in that file, then follow them in order. The outline below is a summary only — the reference file is authoritative.

Phase 1: Decision and Research

  • Step 0: Decide approach (decision_helper.py)
  • Step 1: Research and proposals
  • Step 2: User validation
  • Stop Condition: Stop and request user approval before continuing to Step 3.

Phase 2: Behavioral Baseline (extra vs fast)

  • Step 3 (RED): Run pressure scenarios without skill → Load references/section-2-full-creation-workflow.md → section "Full Mode Behavioral Testing Protocol" (mandatory)
  • Step 4: Document baseline failures

Phase 3: Creation

  • Step 5: Initialize skill (init.py skill <name> --mode full)
  • Step 6: Create content addressing baseline failures

Phase 4: Behavioral Verification (extra vs fast)

  • Step 7 (GREEN): Run scenarios with skill → Load references/section-2-full-creation-workflow.md → section "Full Mode Behavioral Testing Protocol" (mandatory)
  • Step 8: Fix gaps

Phase 5: Structural Validation

  • Step 9: Validate skill (validate_skill.py) — runs structure + security + tokens in one call

Phase 6: Refinement (extra vs fast)

  • Step 10 (REFACTOR): Combined pressure tests → Load references/section-2-full-creation-workflow.md → section "Full Mode Behavioral Testing Protocol" (mandatory)
  • Step 11: Close loopholes

Phase 7: Packaging

  • Step 12: Quality assessment (quality_scorer.py --format json) — behavioral score derived from Steps 3/7/10 subagent results, not from --behavioral flag
  • Step 13: Package (package_skill.py)
Mode Detection

Priority order:

  1. Explicit flag: --mode fast or --mode full
  2. Skill marker: .skillkit-mode file content
  3. If unknown: stop and ask user to choose fast or full

Section 3: Validation Workflow (Overview)

Use when: Validating existing skill

Steps: Execute validation subset (Steps 3-6)

  1. Validate skill — structure + security + tokens (validate_skill.py, no flags needed)
  2. Progressive disclosure check
  3. Test generation (optional)
  4. Quality assessment (quality_scorer.py)

Note: --security-only and --tokens-only flags are available for Section 7 individual tool use, not for workflow validation steps.

For detailed workflow: See references/section-3-validation-workflow-existing-skill.md

Section 4: Decision Workflow (Overview)

Use when: Uncertain if Skills is right approach

CRITICAL: Agent MUST create a temp JSON file first. The decision_helper.py script does NOT accept inline JSON strings - it requires a file path to a JSON file.

Step-by-step invocation: See references/section-4-decision-workflow-skills-vs-subagents.md

Accuracy: Highest (90-95% confidence).

Process:

  1. Run decision_helper.py with json file.
  2. Answer interactive questions
  3. Receive recommendation with confidence score
  4. Proceed if Skills recommended (confidence >=75%)
  5. If confidence <75% or recommendation is uncertain, stop and ask user whether to continue, switch route, or refine inputs.

For detailed workflow: See references/section-4-decision-workflow-skills-vs-subagents.md

Section 6: Subagent Creation Workflow (Overview)

Use when: Creating new subagent (user explicitly asks or decision workflow recommends)

Prerequisites: Role definition clear, workspace available Quality Target: Clear role, comprehensive workflow, testable examples Time: <15 min with template

8-Step Process:

STEP 0: Requirements & Role Definition

  • Answer: Primary role? Trigger conditions? Tool requirements?
  • Choose subagent_type from predefined list

STEP 1: Initialize Subagent File

  • Tool: python scripts/init.py subagent subagent-name --path ~/.claude/agents
  • Creates: ~/.claude/agents/subagent-name.md with template
  • Important: Subagents are individual .md files (not directories)
  • Stop Condition: If target file already exists, stop and ask whether to overwrite, rename, or cancel.

STEP 2: Define Configuration

  • Edit YAML frontmatter (name, description, type, tools, skills)
  • Configure tool permissions (minimal but sufficient)

STEP 3: Define Role and Workflow

  • Role definition section
  • Trigger conditions (when to invoke)
  • Multi-phase workflow

STEP 4: Define Response Format

  • Output structure template
  • Tone and style guidelines
  • Error handling

STEP 5: Add Examples

  • At least 1 complete example
  • Input/Process/Output format

STEP 6: Validation

  • YAML validity check
  • Structure verification
  • Completeness review

STEP 7: Testing

  • Test invocation with Task tool
  • Iterate based on results

STEP 8: Documentation & Deployment

  • Create README.md
  • Register in system
  • Stop Condition: Ask for explicit user confirmation before register/deploy actions.

For detailed workflow: See references/section-6-subagent-creation-workflow.md

Show full SKILL.md (518 more words)Show less

Section 5: Migration Workflow (Overview)

Use when: Converting document to skill

Process:

  1. Decision check (Step 0)
  2. Migration analysis (migration_helper.py)
  3. Structure creation
  4. Execute validation steps (5-8)
  5. Package (Step 9)

Stop Condition (Mandatory):

  • Before structure creation or any write/overwrite operation: ask user confirmation.
  • Do not modify files until user confirms.

For detailed workflow: See references/section-5-migration-workflow-doc-to-skill.md

Section 7: Individual Tool Usage

Use when: User needs single tool, not full workflow

Entry Point: User asks for specific tool like "estimate tokens" or "security scan"

Available Tools

Validation Tool:

bash
python scripts/validate_skill.py skill-name/ --format json

Guide: knowledge/tools/14-validation-tools-guide.md

Token Estimator:

bash
python scripts/validate_skill.py skill-name/ --tokens-only --format json

Guide: knowledge/tools/15-cost-tools-guide.md

Security Scanner:

bash
python scripts/validate_skill.py skill-name/ --security-only --format json

Guide: knowledge/tools/16-security-tools-guide.md

Pattern Detector:

bash
# Analysis mode with JSON output
python scripts/pattern_detector.py "convert PDF to Word" --format json

# List all patterns
python scripts/pattern_detector.py --list --format json

# Interactive mode (text only)
python scripts/pattern_detector.py --interactive

Guide: knowledge/tools/17-pattern-tools-guide.md

Decision Helper:

bash
# Analyze use case (JSON output - agent-layer default)
python scripts/decision_helper.py --analyze "code review with validation"

# Show decision criteria (JSON output)
python scripts/decision_helper.py --show-criteria --format json

# Text mode for human reading (debugging)
python scripts/decision_helper.py --analyze "description" --format text

Guide: knowledge/tools/18-decision-helper-guide.md

Test Generator (v1.2: Parameter update):

bash
python scripts/test_generator.py skill-name/ --test-format pytest --format json
  • --test-format: Test framework (pytest/unittest/plain, default: pytest)
  • --format: Output style (text/json, default: text)
  • Backward compatible: Old --output parameter still works (deprecated)

Guide: knowledge/tools/19-test-generator-guide.md

Split Skill:

bash
python scripts/split_skill.py skill-name/ --format json

Guide: knowledge/tools/20-split-skill-guide.md

Quality Scorer:

bash
python scripts/quality_scorer.py skill-name/ --format json

Guide: knowledge/tools/21-quality-scorer-guide.md

Migration Helper:

bash
python scripts/migration_helper.py doc.md --format json

Guide: knowledge/tools/22-migration-helper-guide.md

Subagent Initializer (NEW):

bash
python scripts/init.py subagent subagent-name --path /path/to/subagents

Guide: references/section-6-subagent-creation-workflow.md

Tool Output Standardization (v1.0.1+)

All 9 tools support --format json. Text mode still available via --format text (backward compatible). decision_helper defaults to JSON for automation.

JSON Output Structure:

json
{
  "status": "success" | "error",
  "tool": "tool_name",
  "timestamp": "ISO-8601",
  "data": { /* tool-specific results */ }
}
Quality Assurance Enhancements (v1.2+)

File & Reference Validation:

  • validate_skill.py now comprehensively checks file references (markdown links, code refs, path patterns)
  • package_skill.py validates references before packaging, detects orphaned files
  • Prevents broken references and incomplete files in deployed skills

Content Budget Enforcement (v1.2+):

  • Hard limits on file size: P0 ≤150 lines, P1 ≤100 lines, P2 ≤60 lines
  • Real-time token counting with progress indicators
  • Prevents file bloat that previously caused 4-9x target overruns

Execution Planning (v1.2+):

  • P0/P1/P2 prioritization prevents over-scoping
  • Token budget allocated per file to maintain efficiency
  • Research phase respects Verbalized Sampling probability thresholds (p>0.10)

Quality Scorer Context:

  • Scores calibrated for general skill quality heuristics
  • Target: 70%+ is good, 80%+ is excellent
  • Style scoring may not fit all skill types (educational vs technical)
  • Use as guidance, supplement with manual review for edge cases

Section 8: Mode Selection Guide

Skill TypeRecommended ModeWhy
TDD or discipline skillfullmust resist rationalization under pressure
Code pattern skillfaststructural checks are usually sufficient
API reference skillfastprimarily retrieval accuracy
Workflow orchestration skillfullcomplex flow benefits from pressure checks
Debugging technique skillfastconcise technique with clear method

Full mode adds behavioral testing (pressure scenarios). Use it when discipline enforcement is core to the skill's purpose.

Section 9: Knowledge Reference Map (Overview)

Strategic context loaded on-demand.

Foundation Concepts (Files 01-08):
  • Why Skills exist vs alternatives
  • Skills vs Subagents decision framework
  • Token economics and efficiency
  • Platform constraints and security
  • When NOT to use Skills
Application Knowledge (Files 09-13):
  • Real-world case studies (Rakuten, Box, Notion)
  • Technical architecture patterns
  • Adoption and testing strategies
  • Competitive landscape analysis
Tool Guides (Files 14-22):
  • One guide per automation script
  • Usage patterns and parameters
  • JSON output formats
  • Integration examples

For complete reference map: See references/section-7-knowledge-reference-map.md

Workflow Compliance

Follow workflows sequentially. Sequential steps with gates produce 9.0/10+ quality. Deviations are allowed with user justification.

Flexible entry points:

  • Single tool (Section 7): skip full workflow
  • Validation only (Section 3): run validation subset
  • Subagent (Section 6): streamlined 8-step workflow

Additional Resources

Load reference files on-demand from references/ when detailed implementation guidance is needed.

© rfxlamia, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 71 other files (scripts, references) in skills/skillkit of rfxlamia/skillkit.

  • SKILL.md
  • .claude-plugin/plugin.json
  • commands/skillkit.md
  • commands/validate-plan.md
  • commands/verify.md
  • knowledge/INDEX.md
  • knowledge/application/09-case-studies.md
  • knowledge/application/10-technical-architecture.md
  • knowledge/application/11-adoption-strategy.md
  • knowledge/application/12-testing-and-validation.md
  • knowledge/application/13-competitive-landscape.md
  • knowledge/foundation/01-why-skills-exist.md
  • knowledge/foundation/02-skills-vs-subagents-comparison.md
  • knowledge/foundation/03-skills-vs-subagents-decision-tree.md
  • knowledge/foundation/04-hybrid-patterns.md
  • knowledge/foundation/05-token-economics.md
  • … and 56 more

Open the folder on GitHubat commit 5021813

Compare with similar skills

Skillkit next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Skillkit compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Skillkit this skillrfxlamia/skillkit102—~3.7kAutomated safety check: PassApache-2.0
PR SweepTanStack/ai3.2k—~4.6kAutomated safety check: PassMIT
Code Context Slicingtrailofbits/skills7.4k—~2.1kAutomated safety check: PassCC-BY-SA-4.0
Fable Foremanolsenbrands/fable-foreman142—~5.2kAutomated safety check: PassMIT
Token Doctortechwolf-ai/ai-first-toolkit132—~4.1kAutomated safety check: PassMIT
Review SwarmDimillian/Skills4k1 repos~1.6kAutomated safety check: PassMIT

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Categories

Questions about Skillkit

What does Skillkit do?

Toolkit for creating and validating skills and subagents. An agent skill from rfxlamia/skillkit. Skillkit is an agent skill from rfxlamia/skillkit. Toolkit for creating and validating skills and subagents.

When should I use Skillkit?

Skillkit fits situations like: : creating a new skill (fast; validating an existing skill; deciding Skills vs Subagents; migrating docs to skills.

How do I install Skillkit in Claude Code?

Run `npx skills add rfxlamia/skillkit --skill skillkit -a claude-code`. Or copy the skill folder (skills/skillkit in rfxlamia/skillkit) into .claude/skills/skillkit in your project. Claude Code loads it when a task matches its description.

How do I install Skillkit in Codex?

Run `npx skills add rfxlamia/skillkit --skill skillkit -a codex`. Or copy the skill folder (skills/skillkit in rfxlamia/skillkit) into .agents/skills/skillkit in your project. Codex loads it when a task matches its description.

Can I use Skillkit in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add rfxlamia/skillkit --skill skillkit -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/skillkit, .gemini/skills/skillkit, .github/skills/skillkit and .opencode/skills/skillkit in your project.

What does Skillkit need to run?

Going by SKILL.md and its folder, Skillkit needs the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Skillkit access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Skillkit safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Skillkit use?

Skillkit is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Skillkit use?

About 3.7k tokens (SKILL.md is roughly 15k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 26k tokens, read only when the agent opens those files.

What are the alternatives to Skillkit?

Skills that share tags, products or a category with Skillkit: PR Sweep (TanStack/ai, 3.2k stars), Code Context Slicing (trailofbits/skills, 7.4k stars), Fable Foreman (olsenbrands/fable-foreman, 142 stars) and Token Doctor (techwolf-ai/ai-first-toolkit, 132 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Skillkit?

rfxlamia (a GitHub user) maintains it in rfxlamia/skillkit, which has 102 GitHub stars. The repository holds 2 skills in this directory. The repository was last updated on March 25, 2026.

Source: rfxlamia/skillkit on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.