◎ Discry Score
decisionnode.com
devtools · API
C
0 / 100
DISCOVERY0
COMPREHENSION0
Category leader: 96 (A)
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DEVTOOLS · RANK #23 OF 39

DecisionNode is Needs Work to agents.

Discry independently scored how well an AI agent can discover and understand the DecisionNode 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 · 52/100
OpenAPI specA machine-readable OpenAPI/Swagger spec agents can parse.Fail
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.Fail
.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 · 87/100
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.Fail
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.Pass
Token efficiencyDocs are concise enough to fit an agent context window.Pass

What we found

  • Domain mismatch: the queued domain decisionnode.com resolves to a BrandBucket 'For Sale' parking page, not the product. The real product lives at decisionnode.dev — an agent or human trying the .com first finds nothing usable. This scan assesses the actual product at decisionnode.dev.
  • Strong discovery for a small tool: an agent integrating DecisionNode finds a genuinely well-structured llms.txt at decisionnode.dev — concise (~1.7KB), product-focused, with install commands and direct links to every docs page plus a single-file full-docs markdown. Also listed on the Glama MCP registry.
  • Documentation is available as clean markdown (decisionnode-docs.md), so an agent gets copy-pasteable MCP config for Claude Code, Cursor, Windsurf and Antigravity plus realistic example decisions — without needing to render the JS site.
  • The rendered /docs pages are a client-side SPA: an agent fetching decisionnode.dev/docs directly gets an empty shell. Only the llms.txt and the /decisionnode-docs.md markdown paths carry real content; llms-full.txt and .well-known/mcp.json both return the same empty shell.
  • Error recovery is undocumented: an agent hitting a missing/invalid Gemini key, a quota error, or an embedding failure finds no troubleshooting guidance and would have to recover by trial and error.

What to change

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

  1. 01Fix the domain — redirect decisionnode.com to decisionnode.dev (or publish a canonical pointer). The most-guessable domain currently resolves to a parking page, forfeiting all discovery for anyone who tries .com first. Highest-impact fix.
  2. 02Add an AGENTS.md to the GitHub repo (github.com/decisionnode/decisionnode) with setup and MCP-connection instructions for coding agents. Cheap win worth 3 discovery points and directly on-brand for a tool built for coding agents.
  3. 03Serve a real llms-full.txt (point it at the existing decisionnode-docs.md) and a .well-known/mcp.json manifest declaring the nine MCP tools and their schemas — both paths currently return the SPA shell.
  4. 04Add a troubleshooting / error-recovery section: what to do on a missing or invalid Gemini key, quota/rate-limit errors, and embedding failures (the existing `decide check` and `decide embed` commands can be documented as recovery steps).
  5. 05Document capability boundaries explicitly: Gemini free-tier rate limits, embedding/size limits, and what the tool intentionally does NOT do (not a rules engine, not injected into the system prompt).

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 (Google Gemini, embeddings) Error format documented Rate limits documented Pagination documented Idempotency documented

The only credential is a single Google Gemini API key (free tier) used for embeddings; the local MCP server runs over stdio with no auth. Error response formats, rate limits, pagination, and idempotency keys are not documented, though conflict detection at 75% similarity guards against duplicate or contradictory entries. All nine MCP tools have documented signatures (e.g. add_decision(scope, decision, rationale?, constraints?, global?, force?, project?)).

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