# Milwaukee Tool — API Agent Score

> Score: 58/100 (Grade: D) | Domain: milwaukeetool.com | Rubric: 1.0.0 | Checked: August 13, 2026

Milwaukee Tool scored 58/100 (D), classified "not-ai-ready".

[View full report](https://www.postman.com/ai/ai-ready-apis/company/milwaukeetool)
[All organizations](https://www.postman.com/ai/ai-ready-apis/llms.txt)

## Summary

- Overall: 58/100 (D)
- Classification: not-ai-ready

## Category Scores

- API Design: 50/100 (D)
- Developer Experience: 100/100 (A+)
- Agent Discovery: 69/100 (C)
- Agent Understanding: 61/100 (C)
- Agent Usability: 40/100 (F)

## Check Results

### API Design

- [pass] Security & governance hygiene — Code is formatter-clean with zero linter errors and zero style warnings. Investigated: sdk 100%, wellknown 50%.
- [fail] Schema coverage & depth — no .d.ts found. Investigated: sdk 0%.
- [fail] Example coverage — No README found. Investigated: sdk 0%.
- [skip] Machine-readable, versioned contract — No surface produced evidence for this capability in this run.
- [skip] Auth declared & discoverable — No surface produced evidence for this capability in this run.

### Developer Experience

- [pass] Self-service developer portal — Signup page found at https://www.milwaukeetool.com/signup, but no free tier or sandbox is documented in docs/pricing, so an agent may hit a paywall. Investigated: docs 100%.
- [skip] Quickstart present — No surface produced evidence for this capability in this run.
- [skip] Code samples in docs — No surface produced evidence for this capability in this run.
- [skip] Description completeness — No surface produced evidence for this capability in this run.
- [skip] Changelog published — No surface produced evidence for this capability in this run.

### Agent Discovery

- [pass] llms.txt present, valid & comprehensive — A full-corpus llms-full.txt is published at https://milwaukeetool.com/llms-full.txt, so agents can ingest all your docs in one fetch. Investigated: docs 100%.
- [warn] Registry & SDK presence — No official SDKs were found on npm, PyPI, or GitHub, so agents must call the API by hand. Investigated: sdk 25%, docs 0%, cli 0%.
- [warn] Crawlable / AEO — Sitemap has lastmod on only 100% of entries, or its newest entry is over 90 days old. Investigated: wellknown 50%.
- [skip] Docs reachable, not hard auth-gated — No surface produced evidence for this capability in this run.

### Agent Understanding

- [warn] Agent instructions file (AGENTS.md) — No agents.md or skill.md context file found (nice-to-have for agent operation). Investigated: sdk 50%, wellknown 0%.
- [skip] Machine-readable errors (RFC 9457) — No surface produced evidence for this capability in this run.
- [skip] Operation purpose clarity — No surface produced evidence for this capability in this run.
- [skip] Agent-navigable, token-efficient docs — No surface produced evidence for this capability in this run.
- [skip] Docs structured data — No surface produced evidence for this capability in this run.
- [skip] Description consistency across surfaces — Only 1 surface description(s) with ≥6 tokens available; need at least 2 to compare.

### Agent Usability

- [fail] Runnable collection with test scripts — No README found. Investigated: sdk 0%, platform 0%.
- [skip] Idempotency documented — No surface produced evidence for this capability in this run.
- [skip] Rate-limit signaling — No surface produced evidence for this capability in this run.
- [skip] Pagination documented & consistent — No surface produced evidence for this capability in this run.
- [skip] Sandbox separation — No surface produced evidence for this capability in this run.

## Executive Summary

Milwaukeetool's API program shows some foundational discoverability in place, but two critical gaps are blocking partner and agent integration at the earliest stages: the API contract lacks typed schemas and concrete examples, and there is no runnable, verifiable collection that partners or agents can execute against. Until these are resolved, partners cannot confidently build integrations and AI agents cannot generate correct code without guessing. Prioritize establishing a strongly-typed, example-rich contract and a live, executable collection immediately — these unlock every downstream partner workflow.