| name | text-summarizer |
| description | Summarise a chunk of text down to roughly `length` words using the agent's configured LLM provider. Input shape `{ text: string, length?: number }` on stdin, JSON; output shape `{ summary: string }` on stdout, JSON. Minimal: ~50 lines, no streaming, no retries — a deliberate baseline so the wiring is visible. For a production summariser, fork this and add retries, prompt-injection sanitisation, length validation, and per-model cost tracking. |
text-summarizer
A minimum-viable LLM skill — the smallest amount of code that takes structured input, calls an LLM, and emits structured output.
Contract
Input (stdin, JSON):
{ "text": "...long input...", "length": 60 }
text (string, required) — what to summarise.length (number, optional, default 60) — target word count for the summary.
Output (stdout, JSON):
{ "summary": "..." }
Errors — written to stderr as { "error": "...message..." } and exit code 1.
Required environment
| Var | Purpose |
|---|
ANTHROPIC_API_KEY | Talks to Claude. Swap the SDK call to point at OpenAI / Gemini / your own backend; nothing else changes. |
Run locally
cd examples/text-summarizer
bun install
ANTHROPIC_API_KEY=sk-ant-... echo '{"text":"...","length":40}' | bun run src/index.ts
Adapt this
- Different model vendor — replace
Anthropic with the SDK of your choice; the I/O shape stays.
- Stream output — emit one JSON line per token instead of one final blob.
- Sanitise input — the current code passes
text to the model verbatim; for untrusted callers, strip control characters and cap length before the API call.
