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Rentcast

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

A4.7/5.0
Behavior5/5

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

The description explains the full behavior: fetching the page, extracting title/description/key links, and emitting standard llms.txt markdown. This adds context beyond annotations, which already indicate read-only, idempotent, and non-destructive behavior.

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 efficient: two sentences covering purpose, behavior, and output, followed by a bullet list of use cases. No redundant information.

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?

Given the tool's simplicity (2 parameters, text output, no output schema), the description covers purpose, behavior, output format, and use cases comprehensively. No gaps identified.

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

Parameters4/5

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 adds value by explaining how the parameters are used (url for fetching, max_links for controlling entries), lifting the score above the baseline of 3.

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 a production-ready llms.txt file for any URL, specifying the verb, resource, and target. It distinguishes from siblings like ai_visibility_check and scan_competitor_ai_presence by focusing on file generation rather than analysis.

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, drafting for own project, auditing competitor. While it doesn't explicitly state when not to use or alternatives, the use cases are clear and helpful.

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

A3.9/5.0
Disambiguation4/5

Most tools have distinct purposes, but some overlapping function sets (e.g., multiple Polymarket tools, multiple ask/research tools) could cause confusion. However, descriptions are detailed enough to differentiate.

Naming Consistency4/5

Naming is mostly consistent with snake_case and verb+noun patterns, but a few tools start with nouns (polymarket_*, pipeworx_*), creating minor inconsistency.

Tool Count3/5

At 32 tools, the server feels heavy and covers many disparate domains. While each tool has its place, the high count strains coherence.

Completeness2/5

Given the server name 'Rentcast', only two tools relate to rental data. The rest cover unrelated domains, leaving a major gap for the intended primary purpose.

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