Prioritycommerceprioritycommerce.com

ScoredSep 24, 2026, 05:41 PM

Prioritycommerce's API program has meaningful strengths in crawlability and documentation discovery, but two critical gaps are limiting partner and agent adoption: the absence of any runnable, executable API surface means partners and AI agents cannot take a first action without manual effort, and the missing machine-readable security and agent-context files leave both humans and automation without the guardrails and instructions they need to build confidently. Addressing the runnable truth gap and the discoverable documentation front door should be the immediate priorities to unlock self-serve partner onboarding.

API DesignA clean, typed, well-governed API contract agents can reason about0 pass0 warn1 fail40F

Signal	Points	Findings	Rationale
Security & governance hygienevia wellknown	0/15	No security.txt found at /.well-known/security.txt or /security.txt, so there's no machine-readable security contact for agents or researchers. Investigated: wellknown 0%. Fix: Publish an RFC 9116 security.txt with a Contact line and a future Expires date.	No leaked secrets, no critical lint violations, no OWASP API Top-10 spec smells, and a published vulnerability-disclosure channel.
Machine-readable, versioned contract	—/25	No surface produced evidence for this capability in this run.	A current OpenAPI version with a declared versioning scheme lets agents reason about the contract.
Schema coverage & depth	—/25	No surface produced evidence for this capability in this run.	Typed, complete request/response schemas are what make agent function-calling possible.
Auth declared & discoverable	—/25	No surface produced evidence for this capability in this run.	Agents can only call an API when they can determine its auth posture — a declared scheme, or an explicit statement that none is required.
Example coverage	—/10	No surface produced evidence for this capability in this run.	Examples carry shape semantics schemas under-specify — for humans and agents alike.

Developer ExperienceThe context both developers and agents need to integrate fast — onboarding, code samples, complete descriptions and worked examples1 pass0 warn1 fail64C

Signal	Points	Findings	Rationale
Self-service developer portalvia docs	29/29	Self-service signup available at https://prioritycommerce.com/contact/, but no free tier or sandbox is documented, so an agent may hit a paywall before the first call. Investigated: docs 100%.	A first call without a human in the loop — self-serve credentials, a free tier, or an API that needs none.
Quickstart presentvia docs	0/25	No quickstart or getting-started page found at the conventional docs paths, so new developers and agents have no obvious first step. Investigated: docs 0%. Fix: Publish a single-page quickstart that goes from zero to a first successful API call.	A quickstart is the fastest path from landing page to first successful call.
Code samples in docs	—/18	No surface produced evidence for this capability in this run.	Multi-language samples shorten time-to-first-call.
Description completeness	—/15	No surface produced evidence for this capability in this run.	Complete descriptions are the context humans and agents need to use endpoints.
Changelog published	—/13	No surface produced evidence for this capability in this run.	A published changelog lets partners track changes without surprise.

Agent DiscoveryPartners and their agents can find your APIs — llms.txt, registries, crawlable and reachable docs1 pass2 warn1 fail67C

Signal	Points	Findings	Rationale
Docs reachable, not hard auth-gatedvia docs	30/30	All 1 pages are publicly accessible. Investigated: docs 100%.	Agents can only index and fetch docs they can reach — past auth gates and over correct HTTP semantics.
llms.txt present, valid & comprehensivevia docs	22.5/30	No llms-full.txt was found at any candidate origin, so agents can't grab your full docs in one fetch. Investigated: docs 75%. Fix: Publish a concatenated, agent-readable copy of your documentation at /llms-full.txt on your docs site.	A valid, comprehensive llms.txt is the machine-readable entry point for agents.
Crawlable / AEOvia wellknown	6/12	No sitemap found via robots.txt or /sitemap.xml on the docs host, so AI search engines have no crawl map for your docs. Investigated: wellknown 50%. Fix: Publish an XML sitemap and reference it from robots.txt.	Bots allowed plus a fresh sitemap make docs findable by agent crawlers.
Registry & SDK presencevia docs	0/28	Not indexed on Context7 — agents can't pull this API's docs on demand via Context7. Investigated: docs 0%, sdk 0%, cli 0%. Fix: Submit the docs to context7.com so coding agents can retrieve up-to-date docs on demand.	Listing in MCP registries and publishing SDKs puts the API where agents and their tooling look.

Agent UnderstandingAgents can correctly interpret your APIs — machine-readable errors, consistent descriptions, structured data, parseable docs1 pass0 warn1 fail74B

Signal	Points	Findings	Rationale
Agent-navigable, token-efficient docsvia docs	22/22	All 1 pages contain server-rendered content. Investigated: docs 100%.	Server-rendered, clean, small-footprint docs are what an agent can cheaply fetch and parse correctly.
Agent instructions file (AGENTS.md)via wellknown	0/10	No AGENTS.md at the site root or /.well-known/, so coding agents have no ready-made setup and usage instructions. Investigated: wellknown 0%. Fix: Publish an AGENTS.md with setup, auth, and usage instructions a coding agent can follow.	An AGENTS.md gives coding agents explicit setup, auth, and usage instructions to interpret and operate the API — beyond llms.txt's link index.
Machine-readable errors (RFC 9457)	—/28	No surface produced evidence for this capability in this run.	RFC 9457 problem details and a documented error-code inventory let agents parse failures without burning tokens.
Operation purpose clarity	—/25	No surface produced evidence for this capability in this run.	Agents select the right endpoint from its summary + operationId; clear, named operations make tool-selection reliable — the strongest driver of correct tool choice.
Docs structured data	—/8	No surface produced evidence for this capability in this run.	Structured data (JSON-LD/schema.org) on docs pages gives agents an unambiguous parse target and is what answer engines cite. Detected on the JS-rendered head (Firecrawl) for a bounded page budget, so JS-injected JSON-LD is now caught; pages we can't render are excluded rather than failed.
Description consistency across surfaces	—/7	Only 0 surface description(s) with ≥6 tokens available; need at least 2 to compare.	Every surface tells the same story about what the product is.

Agent UsabilityAgents have the context to use your APIs reliably, not just find them0 pass0 warn1 fail40F

Signal	Points	Findings	Rationale
Runnable collection with test scriptsvia platform	0/9	No public Postman workspace found for the org, so there's no runnable collection an agent can execute against. Investigated: platform 0%. Fix: Publish at least one public Postman workspace and link it from your developer portal so agents can use Run-in-Postman.	A public, maintained collection with assertions is runnable truth agents validate against.
Idempotency documented	—/27	No surface produced evidence for this capability in this run.	Documented idempotency lets agents retry safely.
Rate-limit signaling	—/22	No surface produced evidence for this capability in this run.	Machine-readable rate-limit headers let agents throttle adaptively.
Pagination documented & consistent	—/22	No surface produced evidence for this capability in this run.	Consistent, documented pagination lets agents traverse collections.
Sandbox separation	—/20	No surface produced evidence for this capability in this run.	An isolated environment lets agents exercise destructive operations safely.

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