My Custom Skill

This is a template for creating a custom agent skill.

How Skills Work

There are two valid skill patterns in the current architecture:

Pattern A: Prompt-Only (Recommended)

No script field in frontmatter. This SKILL.md is injected into the LLM's context when activate_skill is called. The LLM then uses built-in atomic tools (read, write, append, list, grep, ask_env) to accomplish the task.

This is the primary extension mechanism — like Claude Code's slash commands.

Pattern B: Script

Add script: scripts/my-script.py to frontmatter. The script is executed as a cached in-process module via entrypoint(argv, ctx) when available, with dynamic wrapper/subprocess fallback. It should communicate via the returned stdout string and file I/O under ctx.workspace_root. Scripts cannot access the LLM or environment router directly — use this only for deterministic computation.

Behavioral Guidelines (Edit for Your Skill)

When this skill is activated:

1. Use ask_env to query the environment for relevant information.
2. Use read / write / append to persist state.
3. Use execute_skill_script for deterministic computation when a script exists.
4. Call finish with a summary when finished.

Example: A "Daily Journal" Skill

When activated, the agent should:

1. ask_env with instruction: "What happened recently? Summarize recent events."
2. read path journal.jsonl to load previous entries if it exists.
3. append path journal.jsonl to add today's entry.
4. finish with summary of what was journaled.