Bolt scored 99/100 on the DocsAlot benchmark report across 22 published checks. This Help center benchmark shows where agents can use these docs cleanly and where the biggest points of friction still are.
This report passes 18 of 22 checks, with 2 warnings, 1 failed checks, and 1 skipped checks still shaping the next score lift.
Help-center documentation now does double duty: it supports humans directly and powers support agents, AI search, and onboarding flows behind the scenes. This benchmark shows whether the docs are structured well enough to keep support interactions self-serve.
Good help-center documentation is easy to discover, fetch, and follow, with clear hierarchy, concrete recovery paths, and enough task detail that users and agents can solve issues without escalation.
These are the clearest signals behind the current score. Start with the strengths that already support discovery and implementation, then use the gaps below to prioritize the fixes most likely to improve AI readability and self-serve onboarding.
For the broader pattern behind these wins, review AI-readable documentation and compare this page with the full docs benchmark leaderboard.
If you want to improve the system behind these gaps, start with API docs automation, the OpenAPI to CLI generator, and this guide to making docs AI-readable.
Open each category to review the checks behind the score and see exactly where agents still hit friction.
Can an agent read the page without losing important context?
All 10 sampled pages contain server-rendered content
All 9 pages under 50K chars (median 3K, max 9K)
All 10 sampled pages convert under 50K chars (median 3K, 0% boilerplate)
1 of 10 sampled pages have content starting past 50% (worst 107%)
Can an agent tell whether the docs are fresh and trustworthy?
llms.txt covers 100% of 76 sitemap doc pages; 1 llms.txt links not in sitemap (may indicate stale links or incomplete sitemap)
1 of 9 pages have minor content differences between markdown and HTML
All 11 endpoints have appropriate cache headers
Can an agent trust that URLs will stay predictable?
All 10 sampled pages return proper error codes for bad URLs
No redirects detected across 10 sampled pages
Can an agent access the docs without getting blocked?
All 10 sampled pages are publicly accessible
All docs pages are publicly accessible; no alternative access paths needed
Can an agent understand how the page is organized?
No tabbed content detected across 10 sampled pages
No tabbed content found; header quality check not applicable
All 0 code fences properly closed across 10 pages
Can an agent fetch a clean text version of the docs?
9/9 sampled pages support .md URLs (100%)
9/9 sampled pages support content negotiation (100%)
Can an agent find the right starting point?
llms.txt found at 1 location(s)
llms.txt contains parseable links but doesn't fully follow the proposed structure: https://support.bolt.new/llms.txt: No blockquote summary found
llms.txt is 12,219 characters (under 50,000 threshold)
All 10 same-origin sampled links resolve (78 total links)
10/10 same-origin sampled links point to markdown content (100%) (1 external link excluded)
llms.txt directive found in all 9 sampled pages, near the top of content; 1 failed to fetch
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Compare related benchmark reports, then move into the guides and tools that improve documentation benchmark scores.
92/100 score in Productivity. Open the full documentation benchmark report.
91/100 score in Productivity. Open the full documentation benchmark report.
91/100 score in Productivity. Open the full documentation benchmark report.
Compare this documentation benchmark report with other public docs benchmark results.
Score your own API docs or developer docs and open the full public report.
See how docs, SDKs, CLIs, and agent-facing outputs can ship from one OpenAPI-driven system.
Use the CLI page when the benchmark gaps are really onboarding and implementation gaps.
Use this guide when you want to improve the same categories this benchmark scores.
DocsAlot helps teams improve help centers, developer docs, API docs, and CLI docs so they are easier for humans to use and easier for agents to read.