Loading
Example custom agent skill — a template to get started.
Recommended by author
This prompt takes no variables — just pick a model and run.
# 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 (bash, codegen, workspace_read/write, glob, grep) to accomplish the task. This is the **primary extension mechanism** — like Claude Code's slash commands. ### Pattern B: Subprocess Script Add `script: scripts/my-script.py` to frontmatter. The script is executed as a subprocess with `--args-json` and must communicate via stdout (JSON) and file I/O in the agent workspace (`AGENT_WORK_DIR`). Scripts **cannot** access the LLM or environment router — use this only for deterministic computation. ## Behavioral Guidelines (Edit for Your Skill) When this skill is activated: 1. Use `codegen` to query the environment for relevant information. 2. Use `workspace_read` / `workspace_write` to persist state. 3. Use `bash` to run any computation or data processing. 4. Call `done` with a summary when finished. ## Example: A "Daily Journal" Skill When activated, the agent should: 1. `codegen` with instruction: "What happened recently? Summarize recent events." 2. `workspace_read` path `journal.jsonl` to load previous entries. 3. `workspace_write` path `journal.jsonl` to append today's entry. 4. `done` with summary of what was journaled.
Running prompts needs a free account.
Sign in and we'll stream the response from Claude Sonnet 4.6 right here — no config needed for the platform models.
Example custom agent skill — a template to get started.
# 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 (bash, codegen, workspace_read/write, glob, grep) to accomplish the task. This is the **primary extension mechanism** — like Claude Code's slash commands. ### Pattern B: Subprocess Script Add `script: scripts/my-script.py` to frontmatter. The script is executed as a subprocess with `--args-json` and must communicate via stdout (JSON) and file I/O in the agent workspace (`AGENT_WORK_DIR`). Scripts **cannot** access the LLM or environment router — use this only for deterministic computation. ## Behavioral Guidelines (Edit for Your Skill) When this skill is activated: 1. Use `codegen` to query the environment for relevant information. 2. Use `workspace_read` / `workspace_write` to persist state. 3. Use `bash` to run any computation or data processing. 4. Call `done` with a summary when finished. ## Example: A "Daily Journal" Skill When activated, the agent should: 1. `codegen` with instruction: "What happened recently? Summarize recent events." 2. `workspace_read` path `journal.jsonl` to load previous entries. 3. `workspace_write` path `journal.jsonl` to append today's entry. 4. `done` with summary of what was journaled.