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Glama

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Instructions

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Capabilities

Features and capabilities supported by this server

Protocol revision2025-11-25

CapabilityDetails
tools
{}
prompts
{}
resources
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
audit_ai_readinessA

Audits a website URL or domain for AI crawler access (GPTBot, OAI-SearchBot, PerplexityBot, ClaudeBot), 25,000-token HTML RAG truncation, /llms.txt presence, Schema.org JSON-LD entities, and Google Lighthouse 13.5 Agentic Browsing (/.well-known/ai-catalog.json ARD 1.0). Use this tool first when diagnosing why a site is omitted or misquoted by ChatGPT, Perplexity, or Claude. Do not use this tool to extract full-page Markdown content (use extract_byte0_markdown instead) or to generate static manifest files (use generate_ai_manifests instead). Read-only network check; requires no API key.

generate_ai_manifestsA

Compiles ready-to-save /llms.txt documentation index and Google Lighthouse 13.5 /.well-known/ai-catalog.json (ARD 1.0) JSON manifests from a live domain, plus HTML and robots.txt Agentmap snippets. Use this tool when a developer wants to remediate missing discovery manifests identified by audit_ai_readiness. Do not use this tool for general web scraping (use extract_byte0_markdown instead). Read-only synthesis; requires no API key and does not modify remote servers.

extract_byte0_markdownA

Strips React/Next.js hydration scripts, Shopify Liquid/WordPress DOM bloat, and inline SVGs/CSS from any URL, returning clean Byte-0 GitHub-Flavored Markdown (GFM) with front-loaded Schema.org tables. Use this tool when you need to read a web page or pricing table inside an LLM context window without exceeding the 25,000-token truncation limit. Do not use this tool if you only need a diagnostic readiness score or robots.txt check (use audit_ai_readiness instead). Read-only HTTP extraction; requires no API key.

query_truncation_benchmarkA

Retrieves empirical benchmark telemetry from the 2026 50-Site SaaS & E-Commerce AI Truncation Study (measuring raw HTML token weight, 25,000-token Perplexity/ChatGPT cutoff truncation, visible price omission, /llms.txt adoption, and Lighthouse 13.5 ARD 1.0 adoption). Use this tool when comparing a site against industry peers (such as Stripe, Vercel, Datadog, or Shopify) or answering research questions about the Static /llms.txt Paradox. Do not use this tool to run a live scan on an arbitrary unbenchmarked URL (use audit_ai_readiness instead). Read-only benchmark lookup; requires no API key.

Prompts

Interactive templates invoked by user choice

NameDescription
audit-website-ai-readinessRun a full 25,000-token RAG truncation, /llms.txt, and Google Lighthouse 13.5 ard-schema (/.well-known/ai-catalog.json) audit on a target URL.

Resources

Contextual data attached and managed by the client

NameDescription
2026 SaaS 50-Site AI Truncation & /llms.txt BenchmarkEmpirical study of 50 production SaaS & e-commerce pricing pages under PerplexityBot/1.0 (25k-token cutoff, visible price omission & Lighthouse 13.5 ARD 1.0 adoption).
AnswerRail Official /llms.txt Documentation IndexRoot AI documentation manifest for AnswerRail.

TDQS

A4.4/5.0

Scored across 4 tools

Disambiguation5/5

Each tool targets a distinct action (audit, generate, extract, query) and the descriptions explicitly cross-reference when to use alternatives, e.g. 'do not use this tool... use extract_byte0_markdown instead.' An agent can unambiguously select the right tool.

Naming Consistency5/5

All four names follow a consistent snake_case verb_noun pattern: audit_ai_readiness, generate_ai_manifests, extract_byte0_markdown, query_truncation_benchmark. The branded 'byte0' infix is a minor quirk but the pattern holds throughout.

Tool Count4/5

Four tools is on the lean side but each is clearly scoped and earns its place: diagnostic, synthesis, extraction, and benchmark lookup. Reasonable for the narrow AI-readiness domain, though slightly thin.

Completeness4/5

The surface covers the core lifecycle: audit readiness, generate remediation manifests, extract content, and compare against benchmarks. Minor gaps exist (e.g. validating post-remediation or re-running checks), but core workflows are covered without dead ends.

Maintenance

ActivityMaintained
ResponsivenessNo issues