◎ Discry Score
temporal.com
infrastructure · API
A
0 / 100
DISCOVERY0
COMPREHENSION0
Category leader: 98 (A)
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INFRASTRUCTURE · RANK #8 OF 68

Temporal is Agent-Ready to agents.

Discry independently scored how well an AI agent can discover and understand the Temporal 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.Partial
llms-full.txtA full-text bundle agents can load in one request.Pass
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.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 landing on docs.temporal.io can fetch any page as clean raw Markdown by appending `.md` to the URL, and has both an llms.txt index (123KB, with descriptions) and a full llms-full.txt corpus (5.3MB) — a top-tier markdown-availability story that almost no API in the directory matches.
  • An agent looking for end-to-end, agent-relevant guidance finds a dedicated `/ai-cookbook` with runnable agentic-loop, tool-call, human-in-the-loop, and durable-MCP-server recipes for Claude and OpenAI — Temporal documents how to BUILD agents, not just how to call an API.
  • An agent needing self-correction logic finds genuinely actionable error-recovery docs: a best-practices error-handling page with explicit retryable-vs-non-retryable decision rules, idempotence design, and per-language (Python/Go/.NET/Ruby/Java/TS) error guides — far beyond a bare error-code table.
  • The only meaningful discovery gap is `.well-known/mcp.json` (404). Temporal is covered by community MCP servers in PulseMCP and Glama (Mocksi Temporal Workflows, stevekinney/temporal-mcp), but there is no first-party MCP manifest at the documented domain.
  • A nuance an agent must navigate: the public OpenAPI/HTTP spec (saas-api.tmprl.cloud) covers only the Cloud Ops control plane (namespaces, users, keys) — individual Workflows and Activities are driven through language SDKs over gRPC, not a REST surface.

What to change

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

  1. 01Publish a first-party `/.well-known/mcp.json` (or a docs-linked official MCP server) so agents can discover Temporal tooling without relying on third-party PulseMCP/Glama listings — the single easiest discovery win remaining.
  2. 02Trim or split llms.txt: at 123KB it exceeds the ~50KB agent-friendly budget. Offer a lean, API-surface-focused index alongside the comprehensive one so token-constrained agents can orient in a single fetch.
  3. 03Add a concise top-level 'core capabilities in 5 minutes' overview (workflows, activities, workers, task queues, signals/queries) to reduce the tokens an agent needs to grasp the durable-execution model before diving into per-language guides.
  4. 04Make the control-plane vs. execution-plane distinction explicit at the top of the Cloud Ops API page (e.g., a callout: 'This API manages account resources — to run Workflows, use an SDK') so agents don't mistakenly expect a REST endpoint for Workflow execution.

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 keymTLS (client certificates)SAML SSO (user access)Service Accounts Error format documented Rate limits documented Pagination documented Idempotency documented

Execution characteristics are thoroughly documented: API key + mTLS auth for the API (plus SAML SSO and Service Accounts for control-plane access), a gRPC error model with explicit retryable/non-retryable Application Failure semantics, per-Namespace rate limits (Actions Per Second / Operations Per Second with named metrics), cursor-based pagination via next_page_token on List APIs, and extensive idempotency guidance (idempotent Activity design plus Workflow ID reuse policies).

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