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Rattlesnakes By Mail: AI Crawler Field Guide

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Match a free-text question against the claims published on Rattlesnakes By Mail, and return the matching claims, or no match when no published claim covers the question. Every question sent to ask is recorded, and a recorded question may be published on the public questions page at Rattlesnakes By Mail. Do not send private or identifying text to ask.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
questionYesA free-text question about crawlers, agents, or claims.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

The description discloses significant non-obvious behavior beyond the annotations: every question is recorded, and recorded questions may be published publicly. This directly informs the caller of privacy consequences. It also states the no-match behavior, giving a complete picture of the tool's execution and result semantics. Annotations are all false, so the description carries the full transparency burden and meets it well.

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 sentences cover the core function, the return behavior, and the critical privacy warning with no filler. The functional behavior is front-loaded, and each sentence earns its place. The structure is well-suited for an agent scanning the definition.

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 one-parameter tool with no output schema, this description is complete: it explains what the tool does, what it returns, when it returns no match, and the side effect of recording/publishing. Nothing critical is missing for correct invocation, and the privacy warning covers the main risk.

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?

The schema already provides 100% coverage with 'A free-text question about crawlers, agents, or claims,' so the baseline is 3. The description adds meaningful parameter-level guidance by warning that the question is recorded and may be published, implying the caller should avoid private or identifying content in the question. This is useful beyond the schema's simple type description.

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's action: match a free-text question against published claims and return matching claims or no match. This distinguishes it from sibling tools like lookup_crawler and identify_user_agent, which target specific entities rather than free-text questions. The title is generic, but the description carries full clarity.

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 makes the intended use explicit: asking questions about crawlers, agents, or claims for matching against published claims. It also provides an important exclusion by warning not to send private or identifying text because questions are recorded and may be published. However, it does not explicitly name alternative sibling tools or state when to prefer them.

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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