◎ Discry Score
sentry.com
devtools · API
A
0 / 100
DISCOVERY0
COMPREHENSION0
Category leader: 96 (A)
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DEVTOOLS · RANK #3 OF 39

Sentry is Agent-Ready to agents.

Discry independently scored how well an AI agent can discover and understand the Sentry 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 · 90/100
OpenAPI specA machine-readable OpenAPI/Swagger spec agents can parse.Pass
llms.txtAn llms.txt index that points agents to the docs that matter.Pass
llms.txt qualityThe llms.txt is focused, current, and well under the size budget.Pass
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.Pass
.well-known/mcp.jsonA discoverable MCP manifest at a well-known path.Fail
MCP registryThe API is listed in a public MCP registry.Pass
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 · 96/100
Task-oriented descriptionsEndpoints described by what they accomplish, not just their shape.Pass
Realistic examplesRunnable, real-world request/response examples.Pass
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.Partial
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.Pass

What we found

  • An agent could discover and onboard to Sentry almost entirely unassisted: robots.txt explicitly opts in to AI (Content-Signal: ai-train=yes, ai-input=yes), a clean API-focused llms.txt ships dedicated 'Instructions for AI Coding Assistants', and every doc page is retrievable as raw Markdown by appending .md to the URL.
  • An official, dereferenced OpenAPI 3.0.1 spec (getsentry/sentry-api-schema) is publicly accessible and auto-generated from the codebase, so an agent can machine-read the full endpoint surface rather than scraping HTML.
  • AGENTS.md is a first-class artifact across the org — present in the root sentry repo and in nearly every SDK repo (sentry-cli, sentry-react-native, sentry-cocoa, sentry-dart, sentry-docs, sentry-mcp) — giving coding agents authoritative, scoped context.
  • Error recovery is genuinely agent-usable: auth and device-flow errors are documented as tables with a dedicated 'Action' column (e.g., 401 → refresh token, 403 → request additional scopes, slow_down → increase interval by 5s) rather than bare status codes.
  • The only naming wrinkle: path parameters use snake_case (organization_id_or_slug) while JSON bodies use camelCase (rateLimit, useCase), so an agent must track two casing conventions — a common-but-inconsistent REST pattern.

What to change

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

  1. 01Add an llms-full.txt (currently 404) with the consolidated Markdown API reference so agents can ingest the full surface in a single fetch instead of crawling per-endpoint .md pages.
  2. 02Publish a .well-known/mcp.json (currently 404) declaring the official Sentry MCP server (mcp.sentry.dev) and its tools/auth, so agents can auto-discover the MCP endpoint without a web search.
  3. 03Document idempotency support (or its absence) for mutating endpoints — agents retrying POST/PUT after a 429 or network failure currently have no guidance on safe retries.
  4. 04Normalize casing or add a one-line note clarifying the path-param (snake_case) vs body-param (camelCase) convention, removing the one ambiguity an agent must infer.

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.

Auth Token (Bearer)OAuth2 (PKCE + device authorization flow)API Keys (legacy HTTP Basic)DSN (for SDK event ingestion)✓ Error format documented✓ Rate limits documented✓ Pagination documented✕ Idempotency documented

Execution documentation is excellent: OAuth2 and device-flow errors are tabulated with explicit recovery actions, rate limits expose a full set of X-Sentry-Rate-Limit-* headers with per-endpoint windows, and cursor pagination via the Link header is clearly specified. Idempotency keys are not documented.

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