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Generate llms.txt

generate_llms_txt
Read-onlyIdempotent

Generate a production-ready llms.txt file for any URL so AI crawlers (ChatGPT, Claude, Perplexity) can index the site cleanly. Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format. Output is a single text blob ready to drop at site-root/llms.txt. Useful for: getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing how an AI crawler would see a competitor.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYesFull URL of the site to summarize, e.g. "https://example.com" or a specific landing page.
max_linksNoMaximum number of link entries to include (default 25, max 50).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Added

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare safe behavior (readOnly, idempotent, non-destructive). The description adds value by explaining the fetch-and-extract process, consistent with annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three concise sentences plus a bullet list of use cases. No redundant words; every sentence earns its place. Front-loaded with the core purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple tool with two parameters and no output schema, the description fully covers purpose, mechanism, output format, and when to use it. No gaps identified.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the description does not add extra meaning beyond what the schema already specifies (url and max_links with defaults). Baseline score applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Generate') and resource ('llms.txt file'), clearly states the action (fetches, extracts, emits), and distinguishes from siblings by outlining unique use cases (client indexing, drafting, competitor auditing).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit context with 'Useful for:' and three concrete scenarios, but does not include when NOT to use it or explicitly name alternatives among the sibling tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

B3.4/5.0
Disambiguation2/5

Many tools have overlapping purposes, such as ask_pipeworx, ask_pipeworx_beta, and deep_research all routing queries, and the polymarket family (arbitrage, edges, edge_tracker, fill_risk) covering similar ground. While descriptions are detailed, an agent could easily select the wrong tool.

Naming Consistency2/5

Tool names mix bare nouns (airlines, airports, flights) with verb phrases (compare_entities, resolve_entity) and standalone verbs (remember, forget), with no consistent verb_noun pattern. Names like ask_pipeworx_beta and scan_competitor_ai_presence are internally inconsistent with the rest.

Tool Count2/5

37 tools is far beyond the typical scope for a single server, and many are unrelated to the aviation theme, suggesting a lack of focus. The core aviation functionality only accounts for 6 of the tools.

Completeness3/5

The aviation tools (airlines, airports, flights, routes, cities, countries) cover basic lookups, but advanced operations like delay statistics or aircraft data are absent. The unrelated tools do not fill these gaps, and the overall surface feels shallow for a server claiming to be an Aviationstack.