◎ Discry Score
braze.com
communication · API
C
0 / 100
DISCOVERY0
COMPREHENSION0
Category leader: 98 (A)
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COMMUNICATION · RANK #16 OF 24

Braze is Needs Work to agents.

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

Discry your API — freeView the docs ↗

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 · 45/100
OpenAPI specA machine-readable OpenAPI/Swagger spec agents can parse.Partial
llms.txtAn llms.txt index that points agents to the docs that matter.Partial
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 · 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

  • Braze offers "Copy for LLM" and "View as Markdown" buttons on documentation pages plus direct links to Claude and ChatGPT — among the most LLM-friendly doc UX seen
  • The llms.txt exists but covers braze.com product/marketing pages (21KB), not the API documentation at braze.com/docs
  • A community-maintained OpenAPI spec exists at braze-community/braze-specification on GitHub but is not officially hosted
  • Documentation is excellent for comprehension: task-oriented endpoint descriptions, clear permissions tables, detailed error handling with recovery steps
  • The fireMCP (Braze Write Server) exists on Glama as a community extension, but no official Braze MCP server

What to change

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

  1. 01Create a dedicated API-focused llms.txt at braze.com/docs covering REST API endpoints and workflows
  2. 02Host the OpenAPI spec officially rather than relying on the community braze-specification repo
  3. 03Create an official Braze MCP server building on the existing fireMCP community work
  4. 04Add AGENTS.md to the braze-inc GitHub org with guidance for integration agents
  5. 05Add llms-full.txt with comprehensive markdown documentation of all API endpoints

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 (Bearer token)✓ Error format documented✓ Rate limits documented✓ Pagination documented✕ Idempotency documented

Braze uses REST API keys as Bearer tokens with scoped permissions. JSON error responses with HTTP status codes. Rate limit of 250K req/hour with endpoint-specific limits. IP allowlisting supported.

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