{"slug": "make-ai-agents-see-your-website", "title": "Make AI Agents See Your Website", "summary": "RevoGrid, a JavaScript data grid library, has adopted llms.txt and Agent Skills to make its documentation accessible to AI coding agents like Codex, Cursor, and Claude Code. The llms.txt file provides a text-first entry point for agents, while the SKILL.md structure offers progressive disclosure of documentation. This approach ensures agents can find the same installation guides, API references, and migration notes that a human developer would read.", "body_md": "AI coding agents are now part of the developer workflow. Whether we like that shift or hate it, users ask Codex, Cursor, Claude Code, GitHub Copilot, and other tools to install packages, wire examples, migrate code, and explain APIs. For [JavaScript data grids](https://rv-grid.com/blog/datagrid), that often means asking an agent to build columns, editors, filters, Pivot views, or Gantt timelines.\n\nWe ran into the obvious problem: the docs were written for people. A person can use the sidebar, search, breadcrumbs, examples, and product context. An agent often starts with a URL and a vague instruction. If it cannot find the right entry point quickly, it guesses.\n\nThere are several ways to make a site easier for agents to use: an MCP server for live retrieval, skill bundles for structured on-demand context, and `llms.txt`\n\nas a public discovery layer.\n\nThat is where `llms.txt`\n\nhelps. It is a public, text-first entry point that tells AI agents where the important documentation lives: installation guides, API reference, examples, migration notes, troubleshooting, full text exports, and any richer machine-readable bundles.\n\nThe goal is not to “optimize for bots” at the expense of people. The goal is to make sure that when a user asks an agent to build with RevoGrid, the agent can find the same source material a careful developer would read first.\n\n`llms.txt`\n\nActually Used?\n[ llms.txt began as a proposal](https://llmstxt.org/), published by Answer.AI co-founder Jeremy Howard in September 2024.\n\nThere is meaningful adoption among major developer platforms:\n\n`llms.txt`\n\nindex`llms-full.txt`\n\nexport.`llms.txt`\n\nindex`llms.txt`\n\nand `llms-full.txt`\n\nfiles.`llms.txt`\n\nand `llms-full.txt`\n\n`llms.txt`\n\nIs For\nUse it to answer these questions quickly:\n\nExample shape:\n\n```\n# Product Documentation\n\n## Primary Docs\n\n- [Installation](https://rv-grid.com/guide/installation): Install and configure the package.\n- [API Reference](https://rv-grid.com/guide/api/revoGrid): Public TypeScript API.\n- [Migration Guide](https://rv-grid.com/guide/migration): Upgrade notes.\n```\n\n`llms.txt`\n\nto a Documentation Site\n`https://rv-grid.com`\n\n.`/llms.txt`\n\n.`.skill`\n\nbundles or MCP instructions.For most docs sites, `llms.txt`\n\ncan be generated from the same content collection, sidebar, or route manifest that powers the website. That is important. If the AI-facing docs drift from the real docs, agents will confidently produce stale answers.\n\n`llms.txt`\n\nIf your product has paid, enterprise, or advanced modules, say so directly. Agents need to know whether a feature is core, Pro, Enterprise, experimental, or deprecated. Ambiguity here turns into broken code later.\n\nFor large docs, a split skill is usually better than asking an agent to read one giant file. The RevoGrid skill gives agents a `SKILL.md`\n\nindex and one reference file per docs page.\n\nThis structure is no longer limited to one agent. [Anthropic introduced Agent Skills](https://www.anthropic.com/engineering/equipping-agents-for-the-real-world-with-agent-skills) as folders containing instructions, scripts, and resources, and later released the format as an open standard. [OpenAI's Codex documentation](https://developers.openai.com/codex/skills) also recommends a `SKILL.md`\n\nfile with optional `references/`\n\n, `scripts/`\n\n, and `assets/`\n\ndirectories. Both describe progressive disclosure: the agent sees a small description first and loads the full skill or individual references only when the task needs them. The format and current ecosystem are documented at [Agent Skills](https://agentskills.io/).\n\nThis is the best format when:\n\nFor coding agents, the better structure is closer to how a human reads docs:\n\n```\nproduct-docs/\n├── SKILL.md\n└── references/\n    ├── getting-started/\n    │   └── installation.md\n    ├── api-reference/\n    │   └── grid.md\n    └── guides/\n        └── migration.md\n```\n\n`SKILL.md`\n\nis the index and operating guide. It explains when to use the docs and links to focused reference files. This mirrors the progressive-disclosure model documented by both [OpenAI](https://developers.openai.com/codex/skills) and [the Agent Skills specification](https://agentskills.io/specification): advertise a small amount of metadata, then load detailed instructions and references only when relevant.\n\nEach file under `references/`\n\nshould represent one real documentation page. The agent can read the index, choose two or three relevant files, and avoid loading a massive corpus into context.\n\nThis improves answer quality because the model sees complete local context for the page it selected: title, URL, description, source path, examples, and surrounding explanation. It also makes failures easier to debug because you can see which reference file the agent used.\n\nThe implementation should be part of your documentation build pipeline. That keeps the work boring, repeatable, and less likely to rot.\n\nAt build time or request time:\n\n`llms.txt`\n\nas a short index.`llms-full.txt`\n\nas the full fallback corpus.`SKILL.md`\n\nplus `references/<section>/<page>.md`\n\n.`SKILL.md`\n\nfolder format; if your target client supports installable `.skill`\n\narchives, also package the directory as a zip with a `.skill`\n\nextension.The output should be deterministic. If the same docs produce different filenames on every build, agents and caches cannot rely on links.\n\nEach split reference file should be self-contained:\n\n```\n# Page Title\n\nURL: https://rv-grid.com/guide/page/\nSource: src/content/docs/guide/page.mdx\nDescription: Short page summary.\n\nPage content starts here...\n```\n\nKeep the original code examples. Remove interactive-only wrappers that do not help in text form. If your docs use MDX components, unwrap or remove them carefully so the remaining Markdown still reads naturally.\n\nThis is not only for bots. Developers are already trying to understand how their docs should work with agents, and there is not much practical writing from teams that have actually wired this into a docs pipeline.\n\nThat is the reason to write about it. Not because another SEO page needs to exist, but because someone else will hit the same problem: they publish a full text export, point an agent at it, and still get an answer that misses the important part.\n\nThe useful searches are real:\n\nThe page should answer those questions directly. If it does that, search visibility is a side effect of being useful, not the whole point.\n\n`llms.txt`\n\nToo Large\nIf `llms.txt`\n\nbecomes another full corpus, it stops being useful as an index. Keep it short and link out.\n\n`llms-full.txt`\n\nA full export is helpful, but it is not enough for large docs. Agents often grep it and miss important context.\n\nReference files need a good `SKILL.md`\n\nor manifest. Without an index, the agent still has to guess which file to open.\n\nDo not write a separate AI manual by hand unless you can maintain it. Generate from the same docs source whenever possible.\n\n`llms.txt`\n\nas `robots.txt`\n\n`llms.txt`\n\nprovides content and navigation; it does not grant or deny crawler access. Keep using `robots.txt`\n\nand the documented controls for each crawler when access policy matters.\n\nThere is no reliable evidence that `llms.txt`\n\nalone improves AI citations or search visibility. The [Ahrefs study](https://ahrefs.com/blog/what-is-llms-txt/), [critical field reports](https://medium.com/@kaispriestersbach/the-llms-txt-is-dead-more-precisely-a-dud-ab7bee4f469c), and [practitioner discussion on Reddit](https://www.reddit.com/r/SEO/comments/1pqi6uv/is_llmtxt_useful_and_beneficial_for_better_ai/) all show why the claim remains disputed. Measure requests in server logs and evaluate agent answers against real tasks instead of assuming an effect.\n\n`llms.txt`\n\nshort and navigational.`llms-full.txt`\n\nas a full fallback.`llms.txt`\n\n.`robots.txt`\n\n, not `llms.txt`\n\n.`llms.txt`\n\nproposal`llms.txt`\n\nimplementation with Markdown page links and a full export.`llms.txt`\n\n`SKILL.md`\n\nformat and validation rules.`llms.txt`\n\n`llms.txt`\n\n`llms.txt`\n\n`llms.txt`\n\n, and Should You Care About It?`llms.txt`\n\nis dead. More precisely: a dud.”The goal is not to feed the model more text. The goal is to help the agent choose the right text.\n\nFor a small project, `llms.txt`\n\nplus clean Markdown pages may be enough. For larger libraries, frameworks, and enterprise components, add levels: a short index, a full fallback corpus, split reference files, and MCP for live retrieval.\n\nThat is the model we use for RevoGrid: make the docs easy for humans to browse and easy for AI agents to discover, select, and read. The fact that major platforms publish `llms.txt`\n\nand formally support Skills gives this approach credibility; honest measurement and multiple retrieval paths keep it grounded.", "url": "https://wpnews.pro/news/make-ai-agents-see-your-website", "canonical_source": "https://dev.to/kumakint/make-ai-agents-see-your-website-1d23", "published_at": "2026-07-10 17:25:20+00:00", "updated_at": "2026-07-10 17:44:48.534751+00:00", "lang": "en", "topics": ["developer-tools", "ai-agents", "large-language-models", "ai-products"], "entities": ["RevoGrid", "Codex", "Cursor", "Claude Code", "GitHub Copilot", "Answer.AI", "Jeremy Howard", "Anthropic"], "alternates": {"html": "https://wpnews.pro/news/make-ai-agents-see-your-website", "markdown": "https://wpnews.pro/news/make-ai-agents-see-your-website.md", "text": "https://wpnews.pro/news/make-ai-agents-see-your-website.txt", "jsonld": "https://wpnews.pro/news/make-ai-agents-see-your-website.jsonld"}}