text-summarizer

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.