◎ Discry Score
akeneo.com.com
commerce · API
D
0 / 100
DISCOVERY0
COMPREHENSION0
Category leader: 95 (A)
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COMMERCE · RANK #12 OF 21

akeneo.com is Poor to agents.

Discry independently scored how well an AI agent can discover and understand the akeneo.com 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 · 24/100
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.Fail
robots.txt AI directivesrobots.txt allows (or explicitly guides) AI crawlers.Fail
SitemapA sitemap so agents can enumerate the docs surface.Fail

Comprehension

55% of score · 88/100
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.Pass
Error-recovery guidanceDocumented failure modes and how to recover from them.Pass
Answer-first formatThe answer leads; preamble does not bury it.Pass
Capability boundariesClear limits — what the API can and cannot do.Pass
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.Pass
Token efficiencyDocs are concise enough to fit an agent context window.Partial

What we found

  • An agent that already has the docs URL would comprehend this API quickly — every error code (400/401/403/404/405/406/409/413/415/422/429) is documented with a realistic JSON body AND explicit recovery guidance, including 429 Retry-After handling and _links.documentation pointers back to the relevant page. This is best-in-class error-recovery documentation.
  • An agent trying to DISCOVER this API would struggle: the docs host (api.akeneo.com, a static Google Cloud Storage site) returns 404 for robots.txt, llms.txt, llms-full.txt, sitemap.xml, and .well-known/mcp.json. There are no agent-oriented discovery signals at all.
  • The one discovery win is a real, publicly downloadable OpenAPI 3.1 specification (JSON/YAML), auto-generating a Postman collection — an agent that finds it gets a complete, current machine-readable contract.
  • Capability boundaries are explicit and agent-friendly: max 100 items per batch, a 10,000-record offset ceiling that returns a 422 telling the agent to switch to search-after pagination, and a 1,000,000-character-per-line limit — an agent learns the limits from docs rather than by failing.
  • No AGENTS.md exists in the akeneo/pim-api-docs repo and no Akeneo MCP server is listed in the major registries (Glama, Smithery, PulseMCP), so an agent has no coding-agent or tool-calling entry point beyond the raw REST spec.

What to change

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

  1. 01Publish an llms.txt at api.akeneo.com covering the core connector flow (create connection → generate token → fetch/patch products, with links to auth, pagination, and the OpenAPI spec). This is the single highest-impact discovery fix and would lift the weakest dimension.
  2. 02Add a robots.txt and sitemap.xml to the GCS-hosted docs site that explicitly allow AI crawlers and list the documentation pages — right now all four discovery files 404, which suppresses agent and search indexing.
  3. 03Add an AGENTS.md to the akeneo/pim-api-docs repository summarizing the auth flow and endpoint scope so coding agents get useful context without parsing the full reference.
  4. 04Publish or register an official Akeneo MCP server (and list it on Glama/Smithery/PulseMCP) to give agents a first-class tool-calling path into the PIM.
  5. 05Surface multi-language request examples (Python, PHP, JS) alongside the curl snippets in the guides — the values are already realistic and copy-pasteable, but curl-only narrative examples limit direct reuse by agents targeting other runtimes.

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.

oauth2bearer_tokenclient_id_secret Error format documented Rate limits documented Pagination documented Idempotency documented

Execution characteristics are documented unusually well: OAuth2 password-grant flow with refresh tokens, a machine-parseable JSON error format (code/message plus a structured errors array), 429 Too Many Requests with a Retry-After header, and two fully documented pagination methods (search-after cursor for high-volume entities, offset/page as default). Idempotency keys are not documented.

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