text-summarizer — independently scanned and version-tracked by SaferSkills.
SaferSkills independently audited text-summarizer (Agent Skill) and scored it 100/100 (green). The audit ran 55 deterministic rules across Security, Supply Chain, Maintenance, Transparency, and Community; it found 0 high-severity and 0 lower-severity findings. The full rule-by-rule trace and per-finding evidence are below. Free, methodology-open.
Findings & checks · 0 flagged
Every scanned point with the score it earned and what moved between them.
First recorded scan — no prior version to compare against.
The primary manifest — the file an agent reads to learn what this artifact does.
A minimum-viable LLM skill — the smallest amount of code that takes structured input, calls an LLM, and emits structured output.
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.
| Var | Purpose |
|---|---|
ANTHROPIC_API_KEY | Talks to Claude. Swap the SDK call to point at OpenAI / Gemini / your own backend; nothing else changes. |
cd examples/text-summarizer
bun install
ANTHROPIC_API_KEY=sk-ant-... echo '{"text":"...","length":40}' | bun run src/index.tsAnthropic with the SDK of your choice; the I/O shape stays.text to the model verbatim; for untrusted callers, strip control characters and cap length before the API call.~30 seconds. Free. No account. Every finding cites a rule and a line of evidence.