4.7 KiB
Script Opportunities Reference — Workflow Builder
Reference: ./script-standards.md for script creation guidelines.
Core Principle
Scripts handle deterministic operations (validate, transform, count). Prompts handle judgment (interpret, classify, decide). If a check has clear pass/fail criteria, it belongs in a script.
How to Spot Script Opportunities
The Determinism Test
- Given identical input, will it always produce identical output? → Script candidate.
- Could you write a unit test with expected output? → Definitely a script.
- Requires interpreting meaning, tone, or context? → Keep as prompt.
The Judgment Boundary
| Scripts Handle | Prompts Handle |
|---|---|
| Fetch, Transform, Validate | Interpret, Classify (ambiguous) |
| Count, Parse, Compare | Create, Decide (incomplete info) |
| Extract, Format, Check structure | Evaluate quality, Synthesize meaning |
Signal Verbs in Prompts
When you see these in a workflow's requirements, think scripts first: "validate", "count", "extract", "convert/transform", "compare", "scan for", "check structure", "against schema", "graph/map dependencies", "list all", "detect pattern", "diff/changes between"
Script Opportunity Categories
| Category | What It Does | Example |
|---|---|---|
| Validation | Check structure, format, schema, naming | Validate frontmatter fields exist |
| Data Extraction | Pull structured data without interpreting meaning | Extract all {variable} references from markdown |
| Transformation | Convert between known formats | Markdown table to JSON |
| Metrics | Count, tally, aggregate statistics | Token count per file |
| Comparison | Diff, cross-reference, verify consistency | Cross-ref prompt names against SKILL.md references |
| Structure Checks | Verify directory layout, file existence | Skill folder has required files |
| Dependency Analysis | Trace references, imports, relationships | Build skill dependency graph |
| Pre-Processing | Extract compact data from large files BEFORE LLM reads them | Pre-extract file metrics into JSON for LLM scanner |
| Post-Processing | Verify LLM output meets structural requirements | Validate generated YAML parses correctly |
Your Toolbox
Python is the default for all script logic (cross-platform: macOS, Linux, Windows/WSL). See ./script-standards.md for full rationale and safe bash commands.
- Python: Full standard library (
json,pathlib,re,argparse,collections,difflib,ast,csv,xml, etc.) plus PEP 723 inline-declared dependencies (tiktoken,jsonschema,pyyaml, etc.) - Safe shell commands:
git,gh,uv run,npm/npx/pnpm,mkdir -p - Avoid bash for logic — no piping,
jq,grep,sed,awk,find,diff,wcin scripts. Use Python equivalents instead.
The --help Pattern
All scripts use PEP 723 metadata and implement --help. Prompts can reference scripts/foo.py --help instead of inlining interface details — single source of truth, saves prompt tokens.
Script Output Standard
All scripts MUST output structured JSON:
{
"script": "script-name",
"version": "1.0.0",
"skill_path": "/path/to/skill",
"timestamp": "2025-03-08T10:30:00Z",
"status": "pass|fail|warning",
"findings": [
{
"severity": "critical|high|medium|low|info",
"category": "structure|security|performance|consistency",
"location": { "file": "SKILL.md", "line": 42 },
"issue": "Clear description",
"fix": "Specific action to resolve"
}
],
"summary": {
"total": 0,
"critical": 0,
"high": 0,
"medium": 0,
"low": 0
}
}
Implementation Checklist
--helpwith PEP 723 metadata- Accepts skill path as argument
-oflag for output file (defaults to stdout)- Diagnostics to stderr
- Exit codes: 0=pass, 1=fail, 2=error
--verboseflag for debugging- Self-contained (PEP 723 for dependencies)
- No interactive prompts, no network dependencies
- Valid JSON to stdout
- Tests in
scripts/tests/