How Jina Reader’s scores are calculated
The full audit trail, recomputed from the verdict data at build time through the same code that produced the leaderboard: verdict × quality × story weight per cell, cells sum to dimension scores, dimensions blend into the PA Score. Every number on the product page is reproducible from this page alone; for why the formula looks like this, see the methodology.
verdict factors: full ×1.0 · partial ×0.6 · disputed ×0.3 · none ×0.0 · n/a excluded from both sides · cell points = weight × quality × factor · cell max = weight × 10
PA Score23/100
Agent-ready 32.3 × 0.30 = 9.69
API quality 0.0 × 0.20 = 0.00
Openness 45.2 × 0.20 = 9.04
Built-in AI 21.1 × 0.15 = 3.17
Automation 6.9 × 0.15 = 1.03
(9.69 + 0.00 + 9.04 + 3.17 + 1.03) ÷ (0.30 + 0.20 + 0.20 + 0.15 + 0.15) = 22.93 ÷ 1.00 = 22.9
Scores are stored to 1 decimal; the product page’s pills round to whole numbers for display. Each dimension below shows the stories, verdicts, and cited evidence behind its number.
Agent-ready32.3/100×0.30 of the PA blend
Outside-in: can YOUR agent reach and drive this product — API, MCP, CLI, headless runs, agent docs.
Point an agent at llms.txt or agent-oriented docsweight 2
2 (weight) × 5 (quality) × 0.6 (partial) = 6.0 of 20 max
- [github] https://github.com/jina-ai/reader“It converts any URL to an **LLM-friendly** input with `https://r.jina.ai/https://your.url`.”
- [github] https://github.com/jina-ai/reader“`x-preset` — apply a pre-packaged option bundle for common scenarios. ... `research` — for AI research agents needing structured, citable output.”
- [probe] https://jina.ai/llms.txt“PROBE llms.txt: HTTP 404 at https://jina.ai/llms.txt”
Run the product headlessly / in CI for automationweight 2
2 (weight) × 6 (quality) × 0.6 (partial) = 7.2 of 20 max
- [github] https://github.com/jina-ai/reader“It converts any URL to an **LLM-friendly** input with `https://r.jina.ai/https://your.url`.”
- [github] https://github.com/jina-ai/reader“A prebuilt image of the open-source branch is published to GitHub Container Registry. It bundles headless Chrome, LibreOffice, and CJK fonts, so you can run Reader without building it yourself.”
- [github] https://github.com/jina-ai/reader“`x-respond-with` — select the output format. ... `frontmatter` returns **Markdown with a YAML frontmatter block**”
- [github] https://github.com/jina-ai/reader“`x-preset` — apply a pre-packaged option bundle for common scenarios. ... `research` — for AI research agents needing structured, citable output.”
- [github] https://github.com/jina-ai/reader“`x-respond-timing` — explicit control over *when* Reader is willing to return. Trade off latency against completeness”
- [community] https://news.ycombinator.com/item?id=48429579“TB – super-fast text-only browser using Jina Reader API: Does not work (404 not found), return to your vibe code session and try again.”
- [community] https://news.ycombinator.com/item?id=48429579“{"code":401,"name":"AuthenticationRequiredError","message":"Authentication is required to use this endpoint. Please provide a valid API key via Authorization header."}”
- [community] https://news.ycombinator.com/item?id=48429579“readableMessage: AuthenticationRequiredError: Authentication is required to use this endpoint. Please provide a valid API key via Authorization header.”
Plug MCP servers into this product so it can use their toolsweight 3
n/a — not applicable to this product: excluded from numerator and denominator
- [probe] https://github.com/jina-ai/MCP“official MCP server documented at https://github.com/jina-ai/MCP”
Connect an agent via an official MCP serverweight 3
3 (weight) × 7 (quality) × 1.0 (full) = 21.0 of 30 max
- [probe] https://github.com/jina-ai/MCP“official MCP server documented at https://github.com/jina-ai/MCP”
Use an official CLIweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Drive the product through a documented public APIweight 3
3 (weight) × 8 (quality) × 1.0 (full) = 24.0 of 30 max
- [github] https://github.com/jina-ai/reader“It converts any URL to an **LLM-friendly** input with `https://r.jina.ai/https://your.url`.”
- [github] https://github.com/jina-ai/reader“`x-respond-with` — select the output format. ... `frontmatter` returns **Markdown with a YAML frontmatter block**”
- [github] https://github.com/jina-ai/reader“`x-preset` — apply a pre-packaged option bundle for common scenarios. ... `research` — for AI research agents needing structured, citable output.”
- [github] https://github.com/jina-ai/reader“`x-respond-timing` — explicit control over *when* Reader is willing to return. Trade off latency against completeness”
- [github] https://github.com/jina-ai/reader“`x-markdown-chunking` — opt-in semantic chunking of the markdown response. Returns a JSON array (or ``-delimited text) of chunks instead of one blob”
- [claimed-docs] https://jina.ai/reader“Use the `x-json-schema` header with a JSON schema definition, or use `x-instruction` header with natural language instructions. Both features work with ReaderLM-v2 to extract specific fields”
- [probe] https://jina.ai/llms.txt“PROBE llms.txt: HTTP 404 at https://jina.ai/llms.txt”
- [probe] https://jina.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://jina.ai/openapi.json, https://jina.ai/swagger.json, https://jina.ai/api/openapi.json, https://jina.ai/.well-known/openapi.json)”
Issue scoped/least-privilege API credentials for an agentweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Build against official SDKsweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
- [github] https://github.com/jina-ai/reader“`x-respond-with` — select the output format. ... `frontmatter` returns **Markdown with a YAML frontmatter block**”
- [github] https://github.com/jina-ai/reader“`x-preset` — apply a pre-packaged option bundle for common scenarios. ... `research` — for AI research agents needing structured, citable output.”
- [claimed-docs] https://jina.ai/reader“Use the `x-json-schema` header with a JSON schema definition, or use `x-instruction` header with natural language instructions. Both features work with ReaderLM-v2 to extract specific fields”
- [probe] https://jina.ai/llms.txt“PROBE llms.txt: HTTP 404 at https://jina.ai/llms.txt”
- [probe] https://jina.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://jina.ai/openapi.json, https://jina.ai/swagger.json, https://jina.ai/api/openapi.json, https://jina.ai/.well-known/openapi.json)”
Subscribe to events via webhooksweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Agent-ready = 58.2 ÷ 180 × 100 = 32.3
API quality0.0/100×0.20 of the PA blend
The programmable surface once an agent is there — machine-readable spec, interactive docs, sandbox, versioning discipline.
Explore an interactive API reference with runnable examplesweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
Download a machine-readable API spec (OpenAPI or equivalent)weight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
Test against a sandbox environment without touching production dataweight 1
1 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 10 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Rely on versioned APIs with a documented deprecation policyweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max
- [community] https://news.ycombinator.com/item?id=40061533“Have you used them? They offer it for free and I don't find their website mentioning API limit”
- [probe] https://jina.ai/llms.txt“PROBE llms.txt: HTTP 404 at https://jina.ai/llms.txt”
- [probe] https://jina.ai/openapi.json“PROBE openapi: all candidate paths 404 (https://jina.ai/openapi.json, https://jina.ai/swagger.json, https://jina.ai/api/openapi.json, https://jina.ai/.well-known/openapi.json)”
API quality = 0.0 ÷ 100 × 100 = 0.0
Openness45.2/100×0.20 of the PA blend
Can you leave, inspect, or self-host — data export, open source, portability.
Do everything through the API that I can do in the UIweight 2
2 (weight) × 7 (quality) × 1.0 (full) = 14.0 of 20 max
- [github] https://github.com/jina-ai/reader“It converts any URL to an **LLM-friendly** input with `https://r.jina.ai/https://your.url`.”
- [github] https://github.com/jina-ai/reader“PDFs and MS Office documents (Word, Excel, PowerPoint) can now be POSTed directly via the `file` body field — no need to host them first.”
- [github] https://github.com/jina-ai/reader“All images on a page that lack an `alt` tag can be auto-captioned by a VLM (vision-language model) and formatted as `![Image [idx]: [VLM_caption]](img_URL)`”
- [github] https://github.com/jina-ai/reader“`x-respond-with` — select the output format. ... `frontmatter` returns **Markdown with a YAML frontmatter block**”
- [github] https://github.com/jina-ai/reader“`x-preset` — apply a pre-packaged option bundle for common scenarios. ... `research` — for AI research agents needing structured, citable output.”
- [github] https://github.com/jina-ai/reader“Route through the SaaS proxy with `-H 'x-proxy: auto'` (key required). Reader's hosted proxy pool rotates residential / datacenter IPs and handles common anti-bot challenges automatically.”
- [github] https://github.com/jina-ai/reader“`x-markdown-chunking` — opt-in semantic chunking of the markdown response. Returns a JSON array (or ``-delimited text) of chunks instead of one blob”
- [claimed-docs] https://jina.ai/reader“Pass your session cookies with the `X-Set-Cookie` header and the Reader forwards them when fetching the URL”
- [claimed-docs] https://jina.ai/reader“Use the `x-json-schema` header with a JSON schema definition, or use `x-instruction` header with natural language instructions. Both features work with ReaderLM-v2 to extract specific fields”
Export all of my data in open formats and leaveweight 3
3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Read the product's source under an open licenseweight 2
2 (weight) × 6 (quality) × 0.6 (partial) = 7.2 of 20 max
- [github] https://github.com/jina-ai/reader“A prebuilt image of the open-source branch is published to GitHub Container Registry. It bundles headless Chrome, LibreOffice, and CJK fonts, so you can run Reader without building it yourself.”
Self-host the core productweight 3
3 (weight) × 8 (quality) × 1.0 (full) = 24.0 of 30 max
- [github] https://github.com/jina-ai/reader“A prebuilt image of the open-source branch is published to GitHub Container Registry. It bundles headless Chrome, LibreOffice, and CJK fonts, so you can run Reader without building it yourself.”
Openness = 45.2 ÷ 100 × 100 = 45.2
Built-in AI21.1/100×0.15 of the PA blend
Inside-out: how agentic the product itself is for its users — built-in assistants, autonomous features.
Get AI-generated insights and suggestions from my data inside the productweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Set up automations that run autonomously in the backgroundweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Delegate tasks to a built-in AI assistant inside the productweight 3
3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Operate the product with natural-language commandsweight 2
2 (weight) × 6 (quality) × 0.6 (partial) = 7.2 of 20 max
- [claimed-docs] https://jina.ai/reader“Use the `x-json-schema` header with a JSON schema definition, or use `x-instruction` header with natural language instructions. Both features work with ReaderLM-v2 to extract specific fields”
- [github] https://github.com/jina-ai/reader“`x-preset` — apply a pre-packaged option bundle for common scenarios. ... `research` — for AI research agents needing structured, citable output.”
Apply a preset configuration tuned for research agents that returns structured, citable outputweight 2
2 (weight) × 8 (quality) × 1.0 (full) = 16.0 of 20 max
- [github] https://github.com/jina-ai/reader“`x-preset` — apply a pre-packaged option bundle for common scenarios. ... `research` — for AI research agents needing structured, citable output.”
- [github] https://github.com/jina-ai/reader“`x-respond-with` — select the output format. ... `frontmatter` returns **Markdown with a YAML frontmatter block**”
- [claimed-docs] https://jina.ai/reader“Use the `x-json-schema` header with a JSON schema definition, or use `x-instruction` header with natural language instructions. Both features work with ReaderLM-v2 to extract specific fields”
Built-in AI = 23.2 ÷ 110 × 100 = 21.1
Automation6.9/100×0.15 of the PA blend
Depth of automation primitives — rules, scheduling, bulk operations, webhooks.
Perform bulk operations across many items at onceweight 2
2 (weight) × 4 (quality) × 0.6 (partial) = 4.8 of 20 max
- [github] https://github.com/jina-ai/reader“Behind the scenes, Reader searches the web, fetches the top 5 results, visits each URL, and applies `r.jina.ai` to it.”
- [github] https://github.com/jina-ai/reader“It converts any URL to an **LLM-friendly** input with `https://r.jina.ai/https://your.url`.”
- [github] https://github.com/jina-ai/reader“PDFs and MS Office documents (Word, Excel, PowerPoint) can now be POSTed directly via the `file` body field — no need to host them first.”
Define rules that trigger actions automatically on eventsweight 3
3 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 30 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Schedule recurring jobs or workflowsweight 2
2 (weight) × 0 (quality) × 0.0 (none) = 0.0 of 20 max
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Version, review, and roll back my automationsweight 1
n/a — not applicable to this product: excluded from numerator and denominator
no evidence cited — the verdict rests on absence of evidence, re-checked on refresh
Automation = 4.8 ÷ 70 × 100 = 6.9