Skip to main content
Glama

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. First observed

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive. The description adds that it fetches the page, extracts content, and produces a standard format, which is consistent and provides useful behavioral context.

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?

The description is three sentences, front-loaded with the primary action, followed by process and use cases. Every sentence adds value with no redundancy or fluff.

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

Completeness4/5

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

The description covers purpose, process, output format, and use cases. It lacks error handling details or edge cases, but for a straightforward generation tool with strong annotations, it is adequate.

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?

The schema already fully describes both parameters (url and max_links). The description restates the URL purpose and mentions default/max for max_links, but does not add substantial new meaning beyond the schema.

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 clearly states the tool generates an llms.txt file for any URL, specifying the action, input, process, and output. It distinguishes itself from siblings by focusing on file generation rather than visibility checks or research.

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 explicitly lists three use cases (client indexing, personal drafting, competitor auditing). It does not explicitly mention when not to use it or provide alternatives, but the context is clear enough.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A3.8/5.0
Disambiguation2/5

Several tools have heavily overlapping purposes, notably ask_pipeworx vs ask_pipeworx_beta vs ask_pipeworx_grounded, and the cluster of polymarket tools covers adjacent prediction-market analysis territory. The PomBase-specific tools are distinct, but the overall set creates real selection ambiguity.

Naming Consistency3/5

Most names follow a readable snake_case style and many use verb-first patterns, but there is notable mixing: ask_pipeworx is a brand-style exception, entity_profile and polymarket_arbitrage are noun-first, and remember/recall/forget form an inconsistent trio. Not chaotic, but not a clean predictable convention.

Tool Count2/5

33 tools is excessive for a server named Pombase, where only get_gene and get_reference actually serve that domain. Even as a broad data-research server, the count is above the 25-tool threshold and includes many auxiliary utilities that feel bolted on rather than part of a focused surface.

Completeness2/5

The PomBase-specific coverage is severely thin: only systematic-ID gene lookup and PubMed-ID reference lookup, with no gene-name search, annotations browsing, phenotype data, or sequence access. The broader Pipeworx surface is extensive, but for the apparent Pombase purpose, agents will frequently hit dead ends.