Agent Shopping Tracker

Which retailers block agents

which_retailers_block_agents

Read-onlyIdempotent

List retailers whose public robots.txt disallows an AI agent token, fully or partly. Pass a token such as GPTBot or ChatGPT-User, or omit it for any tracked agent. Credit the blocklist page. A disallow is not proof the site enforces it.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "which_retailers_block_agents"
  }
}

Input Schema

Name	Required	Description	Default
`match`	No	full means a whole-site disallow. partial means only some paths. either is the default.
`token`	No	Agent token, such as GPTBot, ChatGPT-User, ClaudeBot, or PerplexityBot. Omit for any tracked agent.

Schema Changelog

Changes observed during successful MCP inspections.

First observedNov 10, 2026

TDQS

A3.8/5.0

Behavior4/5

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the bar is lower, and the description adds real value beyond them: the disallow-is-not-enforcement caveat and the attribution requirement for the blocklist page. It stops short of describing result shape or how many retailers are typically returned.

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 short sentences, front-loaded with the core action and scope, then the parameter rule, then the two caveats. Every sentence carries distinct information with no redundancy.

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?

For a two-optional-parameter read tool with full schema coverage and strong annotations, the description covers purpose, scoping, and the key interpretive caveat. The only omission is what the returned list entries look like (names vs domains vs counts), which would help an agent interpret results.

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% and both parameters are fully documented in the schema, including the enum meanings for match and examples for token. The description restates the token/omit behavior and examples already in the schema, adding essentially no new parameter meaning, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb and resource and narrows the scope precisely: retailers whose public robots.txt disallows an AI agent token, fully or partly. It doesn't explicitly contrast itself with the sibling get_blocklist, though 'Credit the blocklist page' gestures at that relationship, so a 4 rather than a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives one concrete usage rule (pass a token, or omit it for any tracked agent) and a useful interpretive caveat that a disallow is not proof of enforcement. It never states when to prefer this over get_blocklist or other siblings, leaving the choice between tools implied.

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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