/SkillAnything

name: skill-anything
description: >
  Automatically generate production-ready Skills for any software, API, CLI tool, library, workflow,
  or service. Use this skill whenever the user wants to create a skill from scratch for a target
  application, convert an existing tool into an agent-native skill, generate skills for multiple
  platforms (Claude Code, OpenClaw, Codex), or automate the full skill creation pipeline including
  analysis, design, implementation, testing, optimization, and multi-platform packaging. Also use
  when the user mentions "skill-anything", "generate a skill for", "make a skill from", "skillify",
  or wants to turn any software into an agent-ready skill. Even if they just say "create a skill
  for X" where X is any tool or API, this skill should trigger.

SkillAnything

Automatically generate production-ready Skills for any target — software, API, CLI tool, library, workflow, or web service. SkillAnything runs a 7-phase pipeline that analyzes your target, designs the skill architecture, implements it, generates test cases, benchmarks performance, optimizes the description, and packages for multiple agent platforms.

Quick Start

**Fully automated** (one command):

Give SkillAnything a target and it handles everything:
- "Create a skill for the jq CLI tool"
- "Generate a skill for the Stripe API"
- "Turn this workflow into a multi-platform skill"

The pipeline runs all 7 phases automatically. Results land in `sa-workspace/`.

The 7-Phase Pipeline

Phase 1: Analyze    → Detect target type, extract capabilities     → analysis.json
Phase 2: Design     → Map capabilities to skill architecture       → architecture.json
Phase 3: Implement  → Generate SKILL.md + scripts + references     → complete skill directory
Phase 4: Test Plan  → Auto-generate eval cases + trigger queries   → evals.json
Phase 5: Evaluate   → Benchmark with/without skill, grade results  → benchmark.json
Phase 6: Optimize   → Improve description via train/test loop      → optimized SKILL.md
Phase 7: Package    → Multi-platform distribution packages         → dist/

See `METHODOLOGY.md` for the full pipeline specification.

Usage Modes

Auto Mode (default)

Runs all 7 phases end-to-end. Provide the target and SkillAnything does the rest:

Target: "the httpie CLI tool"
→ Analyzes httpie --help output, designs command structure, generates skill,
  creates tests, benchmarks, optimizes, packages for 4 platforms

Interactive Mode

Set `auto_mode: false` in `config.yaml`. SkillAnything pauses after each phase for review:

• Phase 1 → "Here's what I found about the target. Look right?"
• Phase 2 → "Here's the proposed skill architecture. Any changes?"
• Phase 3 → "Draft skill ready for review."
• ...continues with user feedback at each step

Single Phase Mode

Run any phase independently:

python -m scripts.analyze_target --target "jq" --output analysis.json
python -m scripts.design_skill --analysis analysis.json --output architecture.json
python -m scripts.init_skill my-skill --template cli --output ./out
python -m scripts.generate_tests --analysis analysis.json --skill-path ./out/my-skill
python -m scripts.run_eval --eval-set evals.json --skill-path ./out/my-skill
python -m scripts.run_loop --eval-set trigger-evals.json --skill-path ./out/my-skill --model <model>
python -m scripts.package_multiplatform ./out/my-skill --platforms claude-code,openclaw,codex

Configuration

Edit `config.yaml` to customize the pipeline. Key settings:

| Setting | Default | Description | |---------|---------|-------------| | `pipeline.auto_mode` | `true` | Run all phases or pause for review | | `target.type` | `auto` | Force target type: api, cli, library, workflow, service | | `platforms.enabled` | all 4 | Which platforms to package for | | `platforms.primary` | claude-code | Primary output platform | | `eval.max_optimization_iterations` | 5 | Max description optimization rounds | | `obfuscation.enabled` | `false` | Obfuscate original scripts with PyArmor |

See `references/schemas.md` for the complete configuration schema.

Platform Output

| Platform | Install Path | Package Format | |----------|-------------|----------------| | Claude Code | `~/.claude/skills/<name>/` | Directory | | OpenClaw | `~/.openclaw/skills/<name>/` | Directory | | Codex | `~/.codex/skills/<name>/` | Directory + openai.yaml | | Generic | anywhere | `.skill` zip |

See `references/platform-formats.md` for platform-specific format details.

Evaluation and Benchmarking

SkillAnything uses the same eval system as the Anthropic skill-creator:

1. **Test cases** with assertions → graded by `agents/grader.md` 2. **Benchmark** comparing with-skill vs baseline → `benchmark.json` 3. **Description optimization** with train/test split → prevents overfitting 4. **Interactive viewer** via `eval-viewer/generate_review.py`

The eval loop is optional (`skip_eval: true` in config) for rapid prototyping.

Scripts Reference

| Script | Phase | Purpose | |--------|-------|---------| | `analyze_target.py` | 1 | Auto-detect and analyze target | | `design_skill.py` | 2 | Generate skill architecture from analysis | | `init_skill.py` | 3 | Scaffold skill directory from templates | | `generate_tests.py` | 4 | Auto-generate test cases and trigger queries | | `run_eval.py` | 5 | Test description triggering accuracy | | `aggregate_benchmark.py` | 5 | Aggregate benchmark statistics | | `generate_report.py` | 5-6 | Generate HTML optimization report | | `improve_description.py` | 6 | AI-powered description improvement | | `run_loop.py` | 6 | Full eval + improve optimization loop | | `quick_validate.py` | 7 | Validate SKILL.md structure | | `package_skill.py` | 7 | Package for single platform | | `package_multiplatform.py` | 7 | Package for all enabled platforms | | `obfuscate.py` | - | PyArmor wrapper for code protection |

Agents

Read these when spawning specialized subagents:

| Agent | Purpose | |-------|--