# My Custom Skill

> Example custom agent skill — a template to get started.

- Skill: `tsinghua-fib-lab/my-custom-skill` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add tsinghua-fib-lab/my-custom-skill`
- Raw SKILL.md: https://api.skillmd.com/api/skills/tsinghua-fib-lab/my-custom-skill/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: AI & ML
- Author: tsinghua-fib-lab (https://skillmd.com/u/tsinghua-fib-lab)
- Updated: 2026-09-10
- Page: https://skillmd.com/skills/tsinghua-fib-lab/my-custom-skill

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# 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.