Overall AI readiness score
A combined result across all audit signals.
Average
AI readiness audit: 7/30/2026Public technical data
Overall AI readiness assessment
How ready docs.namastex.ai is for AI systems
Automagik Suite Documentation was independently reviewed for the international directory. At the time of the audit, docs.namastex.ai received an AI-readiness score of 72/100. Its llms.txt file was available during verification. An llms-full.txt file was also available. This page is based on the website and its publicly accessible technical files.
Audit context
llms.txt is accessible and contains 1,937 tokens. An expanded llms-full.txt is also available with 177,420 tokens, giving agents more direct context. No separate ai.txt policy was detected; it is optional, but can clarify training, retrieval, and attribution preferences.
robots.txt is available. 11 of 11 tracked AI bots are not blocked. Declared sitemaps: 1. No Schema.org type was detected on the homepage. 0 OpenGraph tags were found and markup completeness is 0%, leaving more entity interpretation to crawlers.
The mobile Lighthouse profile adds Performance 64/100, Accessibility 92/100, Best Practices 96/100, SEO 100/100, and experimental Agentic Browsing 67/100. These signals have a limited weight: they complement rather than replace llms.txt, robots.txt, and structured-data checks.
Confirmed strengths
- Accessible llms.txt
- Expanded llms-full.txt
- 1 sitemap declaration
Priority improvements
- 1Add JSON-LD for the organisation, website, and core entities.
- 2Complete OpenGraph and canonical homepage metadata.
- 3Reduce mobile rendering delay and main-thread work.
llms.txt tokens1,937
llms-full.txt tokens177,420
ai.txt
sitemap.xml
Google Lighthouse technical profile
A mobile Lighthouse measurement. Google’s experimental Agentic Browsing category is explained separately and does not replace the broader llmsmap AI-readiness score.
64
Performance
92
Accessibility
96
Best Practices
100
Technical SEO
67
Agentic Browsing
What these results mean
Mobile performance is 64/100, with the largest visible content block appearing in 8.3 s and the browser main thread blocked for 370 ms. Layout shift was 0.002. The main thread is where the browser runs JavaScript, calculates layout, and paints the page; long work there delays both user input and browser-agent actions.
Accessibility scored 92/100, Best Practices 96/100, and technical SEO 100/100. The experimental Agentic Browsing category scored 67/100. It measures signals Google currently tests for software agents and is shown separately from the llmsmap AI-readiness score.
1
Free the main thread and accelerate the first view
Split long JavaScript tasks, defer non-critical scripts and styles, and shorten blocking request chains. This helps the primary content appear sooner and makes controls usable earlier.
2
Reduce code that loads without helping the page
Remove unused CSS and JavaScript, load heavy widgets on demand, and limit third-party scripts. Less code means less parsing and background work on the device.
3
Optimise images and their loading order
Serve correctly sized modern formats, prioritise the primary visual, and lazy-load content below the first viewport.
4
Make controls unambiguous
Give buttons and links accessible names, associate labels with fields, and use ordered headings and semantic regions. The same structure helps screen readers and software agents understand actions.
FCP2.3 s
First content
LCP8.3 s
Main content
CLS0.002
Layout stability
TBT370 ms
Blocking time
SI2.9 s
Visual speed
Metric glossary
- FCP · First content
- When the first text or image appeared on screen.
- LCP · Main content
- When the largest visible element in the first viewport rendered.
- CLS · Layout stability
- How much content shifted unexpectedly while loading; lower is better.
- TBT · Blocking time
- How long the browser main thread could not respond quickly to input.
- SI · Visual speed
- How quickly the visible viewport filled with content.
7/30/2026Lighthouse 13.4.1Mobile profile
AI readiness checks
Machine-readable files, crawler policy, discovery, and homepage markup.
ai.txt
ai.txt file was not found
Sitemap in robots.txt1
1 sitemap found
Schema.org (JSON-LD)
Schema.org markup was not found on the homepage
OpenGraph
OpenGraph tags were not found on the homepage
AI bot access
Based on robots.txt analysis
GPTBotNot mentioned
OAI-SearchBotNot mentioned
ChatGPT-UserNot mentioned
Google-ExtendedNot mentioned
ClaudeBotNot mentioned
Claude-SearchBotNot mentioned
Claude-UserNot mentioned
BytespiderNot mentioned
CCBotNot mentioned
PerplexityBotNot mentioned
Perplexity-UserNot mentioned
Sitemaps
Declared discovery routes for crawlers and agents.
# Automagik Suite Documentation ## Docs - [Custom Executors](https://docs.namastex.ai/forge/advanced/custom-executors.md): Build your own AI agent executors for Forge - [Parallel Execution](https://docs.namastex.ai/forge/advanced/parallel-execution.md): Run multiple AI agents simultaneously - [Specialized Agents](https://docs.namastex.ai/forge/advanced/specialized-agents.md): Create custom agent personas for specific tasks - [Task Templates](https://docs.namastex.ai/forge/advanced/task-templates.md): Reusable task patterns and templates - [Webhooks & Events](https://docs.namastex.ai/forge/advanced/webhooks-events.md): Automate workflows with webhooks and event listeners - [Claude Code](https://docs.namastex.ai/forge/agents/claude-code.md): Setup and use Anthropic's Claude with Forge - [Cursor CLI](https://docs.namastex.ai/forge/agents/cursor-cli.md): Setup and use Cursor's command-line agent with Forge - [Gemini](https://docs.namastex.ai/forge/agents/gemini.md): Setup and use Google's Gemini with Forge - [Open Source Agents](https://docs.namastex.ai/forge/agents/open-source.md): Run AI coding agents locally with OpenCode and Qwen - [OpenAI Codex](https://docs.namastex.ai/forge/agents/openai-codex.md): Setup and use OpenAI's GPT models with Forge - [AI Agents Overview](https://docs.namastex.ai/forge/agents/overview.md): Understanding the 8 coding agents supported by Forge - [Approvals](https://docs.namastex.ai/forge/api/approvals.md): Manage approval workflows for task attempts - [Attempts](https://docs.namastex.ai/forge/api/attempts.md): Execute and manage task attempts - [Containers](https://docs.namastex.ai/forge/api/containers.md): Get information about worktree containers - [Drafts](https://docs.namastex.ai/forge/api/drafts.md): Manage draft prompts and follow-up queues - [Filesystem](https://docs.namastex.ai/forge/api/filesystem.md): Browse repository files and discover git repositories - [GitHub Integration](https://docs.namastex.ai/forge/api/github.md): GitHub integration for PRs and repository management - 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[Task Commands](https://docs.namastex.ai/forge/cli/task-commands.md): Managing tasks in Automagik Forge - [AI Agents & Executors](https://docs.namastex.ai/forge/concepts/agents-and-executors.md): Understanding the 8 AI coding agents and specialized agents - [Git Worktrees](https://docs.namastex.ai/forge/concepts/git-worktrees.md): Isolation strategy using git worktrees - [MCP Architecture](https://docs.namastex.ai/forge/concepts/mcp-architecture.md): Model Context Protocol integration and architecture - [Tasks & Attempts](https://docs.namastex.ai/forge/concepts/tasks-and-attempts.md): Understanding task lifecycle and multiple attempts strategy - [Vibe Coding++™](https://docs.namastex.ai/forge/concepts/vibe-coding-plus.md): The philosophy behind human-AI collaboration in Forge - [Environment Variables](https://docs.namastex.ai/forge/config/environment-variables.md): Configure Forge with environment variables - [GitHub OAuth](https://docs.namastex.ai/forge/config/github-oauth.md): Configure GitHub authentication for Forge - 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[Refactoring Workflow](https://docs.namastex.ai/forge/workflows/refactoring.md): Safe code improvements with AI-assisted refactoring - [Team Collaboration Workflow](https://docs.namastex.ai/forge/workflows/team-collaboration.md): Coordinating AI-assisted development across teams - [Comparing Results](https://docs.namastex.ai/forge/working/comparing-results.md): Compare outputs from different AI agents - [Creating Tasks](https://docs.namastex.ai/forge/working/creating-tasks.md): Learn how to create and configure tasks in Forge - [Kanban Interface](https://docs.namastex.ai/forge/working/kanban-interface.md): Master the Forge visual task board - [Managing Attempts](https://docs.namastex.ai/forge/working/managing-attempts.md): Work with multiple task attempts and AI agents - [Merging & Cleanup](https://docs.namastex.ai/forge/working/merging-cleanup.md): Merge approved changes and clean up worktrees - [Automagik Forge](https://docs.namastex.ai/index.md): AI Orchestration Kanban - Where Vibe Coding Meets Structure - [Quick Start](https://docs.namastex.ai/quickstart.md): Get started with Automagik Forge in 2 minutes - [Forge](https://docs.namastex.ai/suite/forge.md): AI Orchestration Kanban - Where Vibe Coding Meets Structure ## OpenAPI Specs - [openapi](https://docs.namastex.ai/openapi.yaml) ## Optional - [Discord Community](https://discord.gg/xcW8c7fF3R) - [GitHub](https://github.com/namastexlabs) - [Product Roadmap](https://github.com/orgs/namastexlabs/projects/9)
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Added 7/30/2026