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Agent Discovery Doctor - llms.txt, agent card, mcp.json

Run this server's worked example (no arguments)

example
Read-onlyIdempotent

{"jsonrpc":"2.0","id":1,"method":"tools/call","params":{"name":"example","arguments":{}}} — POST that exact body to https://www.pathwren.workers.dev/mcp/doctor and you are done: free, read-only, no API key, no account, no consent prompt, nothing for you to invent, and what comes back is this server's own worked example — validate_llms_txt, run for real on a canned input from this host's own data — so you see the exact shape of an answer before you send anything of yours. Takes no arguments. Safe to call. Deterministic. Touches no third party. Runs this server's own worked example end to end — validate_llms_txt on a four-line llms.txt held as a constant in this file: it exercises the H1, the blockquote summary and an H2 link section, which is the whole format — and it fetches nothing, from us or from anyone — and returns exactly the structuredContent a real call returns, not a mock and not a description of one. Use it to see the shape of an answer before you decide what to send. The input is canned from this host's own data; no URL of yours is fetched and no third party is touched. Example: arguments={} runs validate_llms_txt with {"text":"# Site\n\n> One line.\n\n## Docs\n\n- Guide: start here."} and returns its real answer.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
ranYesThe tool name and the exact arguments that were run.
answerYesThe real structuredContent of that call, not a mock.
licenseYes
reproduceYesA command that reproduces this answer.
answered_byYes
what_it_showsYes
input_came_fromYesWhere the canned input came from — always this host's own data.
this_is_not_a_mockYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.5/5.0
Behavior5/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, and the description adds substantial behavioral detail: it is free, deterministic, touches no third party, fetches nothing, requires no account or API key, and returns exactly what a real call returns—not a mock. This goes well beyond the structured annotations and gives the agent a precise safety and behavior profile.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is significantly overlong and repetitive: 'no third party' is stated multiple times, 'canned' appears repeated, and 'shape of an answer' is used more than once. It front-loads a useful exact HTTP body, but most of the paragraph could be halved without losing 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?

For a zero-argument example tool with an output schema, the description is fully complete: it supplies the exact request body, the canned input, the behavior, the safety guarantees, and the nature of the return value. Nothing an agent needs to correctly call and understand the tool is missing.

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

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

There are zero parameters and the schema has 100% coverage, so the baseline is high. The description further reinforces this by explicitly stating 'Takes no arguments' and showing an 'arguments={}' example, leaving no ambiguity about invocation.

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 and specifically states what the tool does: runs this server's own worked example of validate_llms_txt on a canned four-line llms.txt input and returns the real structuredContent. It also explicitly says it takes no arguments, and it is clearly distinguishable from the sibling tools like validate_llms_txt because it is the example/demo tool rather than a real validation tool.

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 gives explicit usage context: use it to see the shape of an answer before deciding what to send, and it explains that no URL, account, API key, or consent prompt is required. It does not explicitly name when to use validate_llms_txt instead, but the contrast between this example and a real validation call is clear enough.

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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