STEP 1 — Discover relevant skills. Call this FIRST at the start of any task to check whether the registry contains a curated skill that matches. Performs semantic vector search and returns ranked results with similarity scores.

Workflow after this call: • score > 0.6 → strong match — call skills_get_body with that skill_id • score 0.4–0.6 → possible match — inspect description before proceeding • score < 0.4 → no relevant skill — proceed without one

Query tips: be task-specific, not generic. 'write pytest unit tests for a Flask REST API' outperforms 'testing'. Describe what you are trying to accomplish, not what you want to find.

STEP 2 — Load full skill instructions. Call after skills_find_relevant once you have identified the best-matching skill_id.

Returns three fields: • instructions — expert step-by-step guidance; read and follow these • system_prompt_addition — optional context to add to your persona (may be empty) • tier3_manifest — lists available references, scripts, and assets by filename

After loading: apply the instructions. If tier3_manifest lists files that the instructions explicitly reference, fetch them with skills_get_reference, skills_run_script, or skills_get_asset. Most tasks are fully served by the instructions alone — do not load Tier 3 speculatively.

Version pinning: pass version='1.2' to pin to a specific skill version, or use the inline form skill_id='stripe-integration@1.2'. If the requested version is not found, the latest version is returned with a version_note explaining the fallback. Deprecated skills include a deprecation_notice field naming the replacement.

OPTIONAL STEP 2b — Load config schema, variants, and constraints for a skill. Call only when: (a) the user asks to customise skill behaviour, or (b) skills_get_body instructions mention configurable options.

Returns: config_schema (JSON Schema for parameters), variants (alternative skill modes), dependencies (required tools/packages), limitations (known constraints).

Do NOT call this by default — most tasks complete with skills_get_body alone.

STEP 3a — Fetch a reference document bundled with a skill (markdown files: checklists, policies, API specs, examples).

Two-phase use:

1. Call with filename='list' (default) to see the full reference manifest

2. Call again with the specific filename to fetch its content

Only call when: tier3_manifest from skills_get_body lists reference files AND the skill instructions explicitly name one. Do not load references speculatively.

STEP 3b — Execute a helper script bundled with a skill. Script source is NEVER returned — only stdout, stderr, and exit_code.

Two-phase use:

1. Call with filename='list' to see available scripts and their descriptions

2. Call with the specific filename (and optional input_data) to execute

input_data: key-value pairs passed to the script as environment variables. Scripts run sandboxed in an isolated temp directory with a 30-second hard timeout.

Only call when skill instructions direct you to run a specific script.

STEP 3c — Fetch a template or static resource bundled with a skill (markdown templates, config starters, example data files).

Two-phase use:

1. Call with filename='list' (default) to see the full asset manifest

2. Call again with the specific filename to fetch its content

Use the returned content as a starting template — adapt it to the specific task. Only call when skill instructions reference a specific asset file.