◎ Discry Score
personio.com
productivity · API
C
0 / 100
DISCOVERY0
COMPREHENSION0
Category leader: 92 (A)
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PRODUCTIVITY · RANK #19 OF 24

Personio is Needs Work to agents.

Discry independently scored how well an AI agent can discover and understand the Personio API from what’s public — not whether it’s usable. Below: every signal we checked, what’s costing the score, and what to change.

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SCORED UNDER RUBRIC 1.2 · A full re-launch under Discry Score 2.5 — a new behavioral instrument, not comparable to these scores — is in progress.

Discovery

45% of score · 50/100
OpenAPI specA machine-readable OpenAPI/Swagger spec agents can parse.Pass
llms.txtAn llms.txt index that points agents to the docs that matter.Fail
llms.txt qualityThe llms.txt is focused, current, and well under the size budget.Fail
llms-full.txtA full-text bundle agents can load in one request.Fail
AGENTS.mdAn AGENTS.md that tells coding agents how to build on the API.Fail
.well-known/mcp.jsonA discoverable MCP manifest at a well-known path.Fail
MCP registryThe API is listed in a public MCP registry.Partial
robots.txt AI directivesrobots.txt allows (or explicitly guides) AI crawlers.Pass
SitemapA sitemap so agents can enumerate the docs surface.Pass

Comprehension

55% of score · 68/100
Task-oriented descriptionsEndpoints described by what they accomplish, not just their shape.Pass
Realistic examplesRunnable, real-world request/response examples.Partial
Multi-step workflowsDocs that chain calls into complete jobs an agent can follow.Partial
Error-recovery guidanceDocumented failure modes and how to recover from them.Partial
Answer-first formatThe answer leads; preamble does not bury it.Pass
Capability boundariesClear limits — what the API can and cannot do.Partial
Naming consistencyConsistent, predictable naming across endpoints.Pass
Heading hierarchyClean heading structure agents can navigate.Pass
Markdown docsDocs available as clean markdown, not JS-rendered HTML only.Partial
Token efficiencyDocs are concise enough to fit an agent context window.Partial

What we found

  • Personio follows OpenAPI 3.0.0 specification with 29 endpoints and 110 schemas, providing good structural foundation for agent consumption
  • The developer portal on ReadMe.io provides clean, well-organized API reference with v1 and v2 API versioning
  • An auto-generated MCP server exists on Glama via AG2 builder, showing emerging community interest
  • Documentation includes practical integration guides for syncing data, handling events, and shift planning
  • No llms.txt despite the documentation being well-suited for agent consumption

What to change

Prioritized by impact on discoverability. You (or your docs platform) deploy these — Discry never touches your API.

  1. 01Add llms.txt covering core HR API endpoints (employees, absences, attendance)
  2. 02Create llms-full.txt with comprehensive markdown documentation
  3. 03Add .well-known/mcp.json pointing to the Personio MCP server on Glama
  4. 04Improve code examples with realistic values and multiple language support
  5. 05Add error recovery guidance with specific steps for common integration failures

Execution coverage · INFORMATIONAL, UNSCORED

Whether an agent can actually complete a call and recover from errors is the deeper Audit layer — documented here, but not part of the Discry Score.

API key (client_id/client_secret)✓ Error format documented✓ Rate limits documented✓ Pagination documented✕ Idempotency documented

Personio uses client_id and client_secret for API token generation. JSON error responses. Rate limits documented. Cursor-based pagination.

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