--- title: "ora.ai llms.txt, graded: Agent Ready HTML" description: "The ora.ai llms.txt parsed and graded A against the llmstxt.org structure: 7 sections, 25 links, 9.8 KB. Read 2026-11-04." canonical: https://agentreadyhtml.com/llms-txt-index/ora-ai/ site: "Agent Ready HTML" last_updated: 2026-11-05 section: "llms.txt Index" --- # ora.ai llms.txt, graded: Agent Ready HTML > The ora.ai llms.txt parsed and graded A against the llmstxt.org structure: 7 sections, 25 links, 9.8 KB. Read 2026-11-04. Source: https://agentreadyhtml.com/llms-txt-index/ora-ai/ Site: Agent Ready HTML Last reviewed: 2026-11-05 # ora.ai llms.txt In short ora.ai serves a 9.8 KB llms.txt with 7 H2 sections and 25 links, graded A on the llmstxt.org structure (6 of 6 checks). It passes every check. The home page links the file. An llms-full.txt is served too. Read 4 November 2026. **llms.txt** 9.8 KB, 96 lines ```markdown # ora > ora is the standard for optimizing your site so agents can actually use and recommend you. Scan a URL, watch real agents try to use it, and fix what turns them away. ora is how agents choose who to work with. An agent can look up a product's score before integrating, discover agent-ready products by intent, read what other agents experienced, and submit its own feedback. Every score is computed from public URLs, so it reflects what a product actually exposes to agents, not what it claims. For the full public documentation in one file, see https://ora.ai/llms-full.txt. ## What ora supports - Scan a domain, an MCP server URL, or an MCP App, and get a 0-100 score, an A-F grade, and a four-layer breakdown. - Look up a cached score, browse the ranked leaderboard, or discover products by intent. - Search the paid-capability index: pay-per-call API endpoints (x402/MPP) with per-call USD prices and no API key, liveness-checked by rolling unpaid 402 probes - via the `search_capabilities` MCP tool or the directory. - Read agent feedback on a product, and (agents only) submit your own. Limits to know up front: - Public URLs only. ora cannot scan private or internal sites, or login-gated content. - A fresh scan takes about 30 seconds. Some checks ("deep") use live agent and LLM evaluation and resolve asynchronously after that. - Reads are open and need no key. Feedback writes are MCP-only and require agent verification first. ## Ask this website - [Ask](https://ora.ai/ask): search ora's published website evidence with NLWeb v0.55. No visitor credential is required. - [Ask through MCP](https://ora.ai/agents.md#ask-through-mcp): native NLWeb `ask` with `query.text` and optional `context`, `prefer`, and `meta` retrieves website evidence. - [Request examples](https://ora.ai/agents.md#ask-this-website): POST JSON and GET queries, streaming, limits, and retries. - [API documentation](https://ora.ai/openapi.json): complete request and evidence-response schemas for `/ask`. ## Routing Match a task to the right endpoint: - Primary agent interface (all tools, including feedback): MCP server at https://ora.ai/api/mcp - Searching or reading these docs (search_docs, get_docs_page, get_endpoint; read-only): docs MCP server at https://ora.ai/api/docs/mcp - In the browser (WebMCP): every ora page registers site tools via document.modelContext - scan_domain, get_score, get_leaderboard - wrapping the same REST endpoints below - Skills for coding agents (e.g. agent-ready-website): served by the same MCP server (list_skills / get_skill, skill:// resources), same artifacts as https://ora.ai/.well-known/agent-skills/index.json - Agent-ready-website skill, plain markdown (audit a site, fix the ranked checks, re-audit - includes local tunnels): https://ora.ai/skill.md - CLI auditing client (npx ax@0.10 audit ; --min-score gates CI, --tunnel-cmd audits localhost through your own tunnel): https://www.npmjs.com/package/ax - Look up a cached score: GET https://ora.ai/api/score/{domain} (always try this before scanning) - Run a fresh scan: POST https://ora.ai/api/scan (only on a cache miss or an explicit rescan; a 202 with a Location header means deeper analysis is still finishing - poll that URL) - Poll after scanning: GET https://ora.ai/api/score/{domain} until analysisStatus === "complete" - Run a subset of checks or re-verify a fix: POST https://ora.ai/api/scan/checks (body: url + checkIds from /api/checks; no aggregate score) - Discover products by intent: GET https://ora.ai/api/discover?intent=... - Read agent feedback: GET https://ora.ai/api/feedback/{domain} - Run an agent journey (a real agent attempts a curated task against a domain; trajectory streams as SSE): POST https://ora.ai/api/journey/runs, then open the returned stream_url - intents at GET /api/journey/intents, runnable agents at GET /api/journey/agents; partners holding an ora-issued API key can send a custom free-text task instead of a curated intent, shape at https://ora.ai/api/openapi.json (CLI: npx ax@0.10 deep-journey --intent ; MCP: run_journey, then get_journey_run) - Read a finished journey (verdict, step count, trajectory, insight): GET https://ora.ai/api/journey/runs/{id} - Get or create a domain's journey in one call (ora picks the task and the agent; returns the existing journey, or runs one if there is none): POST https://ora.ai/api/journey/domains/{host} - requires an ora-issued partner API key, shape at https://ora.ai/api/openapi.json - Check your partner API key's usage and monthly limits (scans, journeys): GET https://ora.ai/api/usage - requires an ora-issued partner API key, shape at https://ora.ai/api/openapi.json - Discover agentic resources (ARD): POST https://ora.ai/api/ard/search - ARD registry descriptor (endpoints, filters, pagination): GET https://ora.ai/api/ard - ora's ARD catalog manifest: https://ora.ai/.well-known/ard.json (legacy alias: /.well-known/ai-catalog.json) - Full ARD catalog dump (every indexed entry, one document): GET https://ora.ai/api/ard/catalog.json - Draft your own agent discovery files (ard.json, ai-catalog.json, poppy.json; add ?include=all for llms.txt, a robots.txt edit, an API catalog and MCP server cards) for a domain: GET https://ora.ai/api/agent-files/{domain} - page at https://directory.ora.ai/generate, CLI: npx ax@0.10 generate-files , MCP: generate_agent_files - Full check catalog (every check: id, layer, applicability, maturity): GET https://ora.ai/api/checks ``` First 54 of 96 lines. **Parse** graded A, 6 of 6 file: https://ora.ai/llms.txt ora ora is the standard for optimizing your site so agents can actually use and recommend you. Scan a URL, watch real agents try to use it, and fix what turns them away. 7 sections, 25 links, an Optional section. Ora's cached score: 95, grade A+, scanned 5 November 2026. ## The parse ora.ai lists 25 links: 25 point at ora.ai or a relative path, 0 point elsewhere. The hosts it links most: ora.ai (25). | H2 section | Links | | --- | --- | | What ora supports | 0 | | Ask this website | 4 | | Routing | 0 | | Pages | 13 | | Scoring | 2 | | Optional | 5 | | MCP authentication | 1 | ## Grade against the llmstxt.org structure The file passes all six checks. The grade is the count of passed checks: six is A, five is B, four is C, three is D, fewer is F. It measures structure only. Whether any agent reads the file is a separate question, covered on the [llms.txt reference](https://agentreadyhtml.com/llms-txt/). | Check | Result | Detail | | --- | --- | --- | | Starts with an H1 naming the site or project | Pass | H1: ora | | Has a blockquote summary under the H1 | Pass | Blockquote summary found. | | Has at least one H2 section that lists links | Pass | 7 H2 sections, 5 with links. | | At least 80 percent of links point at the same site | Pass | 25 of 25 links stay on ora.ai (100 percent). | | Under 100 KB | Pass | 9984 bytes as served. | | Plain markdown, no HTML | Pass | No HTML document markers in the body. | ## Ora's cached score Ora's cached report for ora.ai gives it **95 of 100, grade A+**, scanned on 5 November 2026. Its Access layer, which holds the read-layer checks below, scored 63 of 65 check points. Read from GET ora.ai/api/score/ora.ai on 5 November 2026. The score is Ora's, not this site's, and the structure grade above is a different measure: it grades the llms.txt file against the llmstxt.org proposal, while Ora's score covers the whole site. [Ora's report for ora.ai](https://ora.ai/score/ora.ai?utm_source=agentreadyhtml.com&utm_medium=referral&utm_campaign=index-entry) has every layer. | Ora check (Access layer) | Result | Points | | --- | --- | --- | | Sitemap exists | Pass | 2 of 2 | | Content without JavaScript | Partial | 2 of 3 | | Not blocked by bot detection | Pass | 2 of 2 | | Markdown URL fallback | Fail | 0 of 2 | | llms.txt exists | Pass | 1 of 1 | | llms.txt formatting | Pass | 2 of 2 | | JSON-LD structured data | Pass | 4 of 4 | | Metadata completeness | Pass | 2 of 2 | | llms.txt links resolve | Partial | 1 of 2 | | Markdown alternate link | Partial | 0 of 1 | | Redirect hygiene | Pass | 1 of 1 | | Page token budget | Pass | 1 of 1 | | Code fence validity | Pass | 1 of 1 | | Content behind auth | Pass | 2 of 2 | | OpenAPI spec published | Pass | 7 of 7 | | Markdown agent docs | Pass | 1 of 1 | | Markdown negotiation with Vary | Fail | 0 of 1 | | Markdown for agent user agents | Fail | 0 of 1 | | Agent crawler reachability | Pass | 2 of 2 | ## Linking and the companion file The home page of ora.ai links the file in its HTML. Ora's lab found (2026-10-19) that 86 percent of llms.txt fetches by agents arrived through a link, so an unlinked file is mostly a file nobody opens. An llms-full.txt is served at the same root. ## How it compares At 9.8 KB the file is larger than 59 percent of the 2,529 plain-text llms.txt files in this edition, and its 25 links put it ahead of 39 percent of them on link count. The home page declares no generator. Size bucket: 2 to 10 KB. Curated example. Category: Agent Tools. Why it is in the index: Linked from every page per Ora; points to llms-full.txt. Owner as listed: Ora. Live file: [https://ora.ai/llms.txt](https://ora.ai/llms.txt?utm_source=agentreadyhtml.com&utm_medium=referral&utm_campaign=index-entry). Read 4 November 2026. If the file has since changed or gone, the live URL is the authority; this page records what the crawl read on that date. - [All entries](https://agentreadyhtml.com/llms-txt-index/) - [Edition 2026-11-04](https://agentreadyhtml.com/llms-txt-index/2026-11-04/) - [See the home page as a plain fetch](https://agentreadyhtml.com/viewer/?url=https%3A%2F%2Fora.ai%2F) ## Sources 1. [ora.ai llms.txt](https://ora.ai/llms.txt?utm_source=agentreadyhtml.com&utm_medium=referral&utm_campaign=entry) https://ora.ai/llms.txt, read 4 November 2026 2. [llms.txt proposal (llmstxt.org)](https://llmstxt.org/) https://llmstxt.org/, read 4 November 2026 3. [Tranco list 746WX (crawl universe)](https://tranco-list.eu/list/746WX) https://tranco-list.eu/list/746WX, read 4 November 2026 4. [Ora: AgentReady launch post (the 86 percent finding)](https://ora.ai/blog/agentready-launch?utm_source=agentreadyhtml.com&utm_medium=referral&utm_campaign=entry) https://ora.ai/blog/agentready-launch, read 4 November 2026 Last reviewed 5 November 2026 Edition Crawl 2026-11-04 Ora reads 2026-11-05 Page updated 2026-11-05 Method How the viewer reads a page, how a file is graded and how a platform is scored: [the method page](https://agentreadyhtml.com/method/).