# People Data Labs — API Agent Score

> Score: 65/100 (Grade: C) | Domain: peopledatalabs.com | Rubric: 1.0.0 | Checked: July 24, 2026

People Data Labs scored 65/100 (C), classified "partially-ready".

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

## Summary

- Overall: 65/100 (C)
- Classification: partially-ready

## Category Scores

- API Design: 75/100 (B)
- Developer Experience: 50/100 (D)
- Agent Discovery: 93/100 (A+)
- Agent Understanding: 58/100 (D)
- Agent Usability: 53/100 (D)

## Check Results

### API Design

- [pass] Schema coverage & depth — 25/25 enums are named types (not bare strings). Investigated: sdk 100%.
- [pass] Example coverage — README is present and includes a runnable quickstart. Investigated: sdk 100%, docs 0%.
- [fail] Security & governance hygiene — No security.txt at /.well-known/security.txt or /security.txt. Investigated: wellknown 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] Changelog published — Newest official SDK activity 1 day(s) ago. Investigated: sdk 100%.
- [warn] Quickstart present — Quickstart page reachable (2 variants scanned starting at https://docs.peopledatalabs.com/docs/quickstart) but no runnable code sample detected in HTML or .md variant. Investigated: docs 50%.
- [fail] Self-service developer portal — No signup page detected across conventional paths (/signup, /sign-up, /register, /get-started, /console/signup, /dashboard/signup, /try, /try-free, /free, /free-trial, /start, /start-free). Investigated: docs 0%.
- [fail] Code samples in docs — No detectable code samples across 20 sampled docs pages. Investigated: docs 0%.
- [skip] Description completeness — No surface produced evidence for this capability in this run.

### Agent Discovery

- [pass] Docs reachable, not hard auth-gated — All 1 pages are publicly accessible. Investigated: docs 100%.
- [pass] Registry & SDK presence — Indexed on Context7 (websites/peopledatalabs, 1585 snippets). Investigated: docs 100%, sdk 67%, cli 0%, mcp 0%, wellknown 0%.
- [warn] llms.txt present, valid & comprehensive — No /llms-full.txt found at the candidate origins. Investigated: docs 75%, sdk 0%.
- [pass] Crawlable / AEO — Docs paths crawlable by all monitored AI agents. Investigated: wellknown 100%.

### Agent Understanding

- [pass] Agent-navigable, token-efficient docs — All 1 pages contain server-rendered content. Investigated: docs 100%.
- [pass] Docs structured data — JSON-LD Article markup on 16/17 assessed pages (94%) with dateModified present (1 JS-rendered). Investigated: docs 100%.
- [warn] Description consistency across surfaces — Mean pairwise description similarity across 2 surfaces (docs, sdk) is 20% (threshold 35% for full credit).
- [fail] Machine-readable errors (RFC 9457) — No single common SDK base error class was found; errors do not share one root. Investigated: sdk 0%.
- [fail] Agent instructions file (AGENTS.md) — No AGENTS.md at the site root or /.well-known/. Investigated: wellknown 0%.
- [skip] Operation purpose clarity — No surface produced evidence for this capability in this run.

### Agent Usability

- [pass] Sandbox separation — Sandbox environments are exposed (sandbox). Investigated: sdk 100%.
- [fail] Idempotency documented — No built-in retry machinery was found; transient failures are not retried. Investigated: sdk 0%.
- [fail] Runnable collection with test scripts — No public Postman workspace discovered for the org. Investigated: platform 0%.
- [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.

## Executive Summary

Peopledatalabs has a strong foundation in API discoverability, but the partner program is held back by two critical gaps: agents and partners cannot reliably understand or act on the API's errors, contracts, or operational patterns, and the onboarding path lacks the self-service portal and code samples needed for partners to get hands-on quickly. Closing the error semantics, agent context, and runnable-truth gaps should come first — they directly determine whether partners and their AI agents can build confidently against the API — followed by tightening the security hygiene and onboarding experience that determine whether partners trust and choose the program at all.