seo-agent
Skill4 starsChanged 8 months agoMITView on GitHub
Agent Engine Optimization (AEO) - audit whether AI agents can discover, understand, and call your product without human assistance. Checks MCP server presence and quality, OpenAPI spec discoverability, llms.txt agent profile, SDK availability, CLI tool discoverability, and developer docs machine-readability. Use when user says "AEO", "agent-friendly", "MCP server", "agent discovery", "AI agent SEO", "llms.txt", "tool use", "agent-readable".
We split this skill into the rules it gives an agent
1 rule. About 0 are common, 1 is distinctive, and 0 are very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈1
Distinctive · estimate
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 74
Verify registration across MCP directories:
≈ “Common” is an estimate: at least 1 in 5 of the 308,232 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
seo-agent — Agent Engine Optimization (AEO)
Key Statistics (2026)
| Metric | Data | Source |
| MCP SDK monthly downloads | Rapid growth (tens of millions) | Anthropic |
| Active MCP servers | 10,000+ | Smithery.ai |
| MCP directories | 7+ active directories | Community |
| AI Agent enterprise adoption | 85% expected | Gartner |
Core Insight
MCP tool descriptions are the PRIMARY signal agents use to select tools—vague descriptions cause agents to skip your tools even if the API is powerful.
AEO Scoring System (0-100)
9 weighted categories determine overall AEO readiness:
| Category | Weight | What's Audited |
| MCP Discoverability | 20% | .well-known/mcp.json exists, tool description quality |
| Directory Presence | 10% | Registration on Smithery.ai (3x), mcp.so (2x), Cursor, PulseMCP, AIXPLORIA, Glama, GitHub Awesome MCP |
| API Machine-Readability | 18% | OpenAPI spec presence, operationId naming, RFC 7807 error format |
| llms.txt Agent Profile | 12% | File exists, includes API/SDK links, capability declarations |
| SDK Coverage | 12% | npm/PyPI packages exist, type definitions, structured READMEs |
| Developer Docs Quality | 10% | Programmatically followable Quickstart, fenced code blocks, auth docs |
| CLI Discoverability | 5% | bin entry in package.json, --help formatting, --json output |
| robots.txt Agent Directives | 5% | Allows known Agent UAs, API paths not blocked |
| Agent DX | 8% | Sandbox mode (no auth required), consistent pagination, <5min to first call |
Audit Process
1. robots.txt Agent Analysis
Checks for explicit allowances for agentic user-agents (Claude-Code-Bot, OpenAI-Operator-Bot) with API paths accessible.
2. MCP Manifest Evaluation
Fetches /.well-known/mcp.json, scores tool descriptions for specificity (80-150 words = high quality).
3. OpenAPI Spec Validation
Checks for spec at standard locations (/.well-known/openapi.json, /openapi.json), validates operationId naming and error format.
4. llms.txt Agent Profile
Parses /.well-known/llms.txt and llms-full.txt for agent-specific fields (MCP-Server, OpenAPI-Spec, Capabilities).
5. SDK Package Verification
Queries npm/PyPI for package presence, checks for TypeScript type definitions and structured README (INSTALL, QUICKSTART, API Reference).
6. CLI Tool Check
Verifies bin entries in package.json, analyzes --help formatting and --json output.
7. Documentation Analysis
Crawls developer docs for programmatic Quickstart, code example formatting, and explicit auth header documentation.
8. Overall Score Calculation
Weights each category and produces final AEO readiness score (0-100).
9. Directory Presence Check
Verify registration across MCP directories:
| Directory | Weight | Check Method |
| Smithery.ai | 3x | Primary Anthropic partner directory |
| mcp.so | 2x | Community curated, high traffic |
| Glama | 1x | MCP marketplace with ratings |
| Cursor Directory | 1x | Cursor IDE integration |
| PulseMCP | 1x | Emerging directory |
| AIXPLORIA | 1x | AI tool directory |
| GitHub Awesome MCP | 1x | Community list |
Directory Presence Score: 0 directories = 0pts, 1-2 = 25pts, 3-4 = 50pts, 5-6 = 75pts, 7+ = 100pts
Output Format
Generates AEO-ANALYSIS.md with:
- AEO Readiness Score — XX/100
- Category Breakdown — Detailed findings for each of 9 categories
- Quick Wins — 1-week effort improvements
- Medium Effort — 1-month timeline improvements
- Architecture Changes — 2-3 month strategic improvements
Reference Files (On-Demand)
- mcp-quality.md — MCP manifest structure, tool description scoring, registration directories
- agent-user-agents.md — Known Agent UAs, robots.txt templates, llms.txt extensions
- openapi-compliance.md — OpenAPI 3.1 requirements, operationId naming, RFC 7807 format
Usage Examples
/seo agent https://clawpond.com
/seo agent https://api.stripe.com
/seo agent https://github.com/anthropics/claude-sdkWhen to Use
Use seo-agent when:
- You want AI agents (Claude Code, OpenAI Operator) to discover your product
- You're building an MCP server and need quality scores
- You're evaluating a vendor's agent-readiness
- You're implementing OpenAPI specs and want agent validation
- You're launching CLI tools or SDKs and want discoverability audits
Other versions1 project uses a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 1
- jsath/claude-skills★ 14same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository25 other files it gives its agents.
- seo-auditSkill
- seo-backlinksSkill
- seo-competitor-analysisSkill
- seo-competitor-pagesSkill
- seo-content-briefSkill
- seo-contentSkill
- seo-data-toolsSkill
- seo-geoSkill
- seo-hreflangSkill
- seo-imagesSkill
- seo-keyword-researchSkill
- seo-localSkill
- seo-monitorSkill
- seo-multiplatformSkill
- seo-pageSkill
- seo-performanceSkill
- seo-planSkill
- seo-programmaticSkill
- seo-rank-trackerSkill
- seo-reportSkill
- seo-schemaSkill
- seo-sitemapSkill
- seoSkill
- seo-technicalSkill
- seo-visualSkill
Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
Reviews can't be read right now.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.