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Opentopography

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).

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, idempotentHint=true, destructiveHint=false. The description adds behavioral details like fetching the page, extracting title/description/key links, and emitting markdown format. It does not contradict annotations and provides useful extra context beyond the structured data.

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 two concise paragraphs: the first explains the tool's action and output, the second lists use cases. No superfluous words, and critical information is front-loaded. Every sentence adds value.

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 tool with 2 simple parameters and no output schema, the description fully covers its behavior: it fetches, extracts, and emits a single text blob. The output format and deployment location are clearly stated. No gaps remain for an agent to invoke the tool correctly.

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% (both parameters described in schema). The description mentions 'for any URL' and 'max link entries' implicitly, but adds little new meaning beyond what the schema already provides. Baseline score of 3 is appropriate given high coverage.

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 specific verbs ('generate', 'fetches', 'extracts', 'emits') and clearly identifies the resource (llms.txt file for a URL). It distinguishes from sibling tools by focusing on AI indexing and a specific output format, making its purpose unambiguous.

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 site indexing, personal project drafting, and competitor auditing. While it doesn't mention when not to use or provide alternative tool names, the stated use cases give clear context for appropriate usage.

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

The tool set has several near-duplicate entries (ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded; five polymarket_* tools), and the server name implies topography while most tools serve unrelated data lookups, making it hard to select the right tool for a task.

Naming Consistency3/5

Most tool names use snake_case and a verb-first style, but there are notable exceptions like 'datasets', 'dem', and 'forget', and the 'pipeworx' prefix is applied inconsistently (pipeworx_feedback, pipeworx_trending vs. ask_pipeworx). The pattern is readable but not fully uniform.

Tool Count2/5

With 34 tools, the count is excessive for a server named Opentopography, especially since only 3 tools (datasets, dem, point_elevation) relate to the implied domain. The bulk of tools belong to a general-purpose data and prediction-market service, creating a severe scope mismatch.

Completeness2/5

For the implied topography domain, the surface is severely incomplete: only dataset listing, a raster fetch, and a point elevation lookup are present, missing expected operations like elevation profiles, point cloud access, or data processing. For the broader Pipeworx domain, coverage is broad but this does not match the server's stated focus.

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