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Estat Japan

by io.github.pipeworx-io

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

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, openWorld, idempotent, and non-destructive. The description adds actionable context: 'Fetches the page, extracts title/description/key links, and emits the standard llms.txt markdown format.' 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?

The description is concise: two sentences capturing purpose, process, and output. Every sentence adds value and is front-loaded with the main action.

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?

With 2 parameters, no output schema, and good annotations, the description explains the output format ('single text blob ready to drop at site-root/llms.txt') and process. Could be considered complete for this simple tool.

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% with clear parameter descriptions. The description repeats the purpose of url and references max_links implicitly ('Maximum number of link entries'). No additional semantic value 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 it generates an llms.txt file for a given URL, with specific verb ('generate'), resource ('llms.txt'), and scope ('for any URL'). It distinguishes from sibling tools like ai_visibility_check by focusing on the llms.txt generation task.

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 use cases ('getting a client's site indexed by AI, drafting llms.txt for your own project, or auditing...'). While it lacks explicit alternatives or 'when not to use', the context is clear enough for an agent to decide.

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

A3.6/5.0
Disambiguation3/5

Many tools have overlapping purposes, especially the ask_pipeworx variants and Polymarket tools, but detailed descriptions help differentiate. Some tools like 'discover_tools' and 'suggest_questions' also have similar discovery roles, causing potential confusion.

Naming Consistency3/5

Names follow snake_case but lack a consistent pattern: some start with verbs (e.g., 'ask_pipeworx', 'compare_entities'), others with nouns (e.g., 'entity_profile', 'recent_changes'), and prefixes like 'pipeworx_' and 'polymarket_' are used sporadically, making the naming scheme mixed but still readable.

Tool Count2/5

35 tools is excessive for a server named 'Estat Japan', which should focus on Japanese statistics. The majority of tools are general-purpose Pipeworx tools, diluting the scope and making the count feel bloated for the stated purpose.

Completeness2/5

The e-Stat tools (list_data_catalog, search_stats, get_metadata, get_data) provide basic read-only access but lack update or delete operations. The inclusion of many unrelated tools leaves significant gaps for Japanese statistics, and the overall surface is incomplete for the server's implied domain.

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