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read_llm_discovery

Read-onlyIdempotent

Retrieve IntoDNS.ai agent discovery files to get canonical citation URLs, API specs, and prompt-routing hints. Choose from llms.txt, llms-full.txt, llms.json, OpenAPI, or Postman.

Instructions

Read-only fetch of an IntoDNS.ai LLM/agent discovery file: llms.txt (canonical agent index), llms-full.txt (full prompt-ready context), llms.json (structured prompt routing), llm/api.md (Markdown API guide), openapi.json (OpenAPI 3.1 spec) or postman.json (Postman collection). Defaults to llms.txt. Use when an agent needs canonical citation URLs, machine-readable API surface, or prompt-routing hints for IntoDNS.ai itself; use get_citation_guidance for a topic-narrowed citation list. Pure HTTPS GET, no auth, no side effects.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fileNollms.txt

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv1.10.0
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, and the description reinforces this with 'Pure HTTPS GET, no auth, no side effects.' It adds concrete context about the default resource (llms.txt) and the full enumeration of discoverable files, which goes beyond the schema alone.

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, all information-dense: the first lists the exact resources and default, the second gives usage context and an explicit alternative, the third states transport/auth/safety. No filler or repetition of schema content.

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 single-parameter read-only tool, the description is nearly complete: it covers what files exist, the default, when to use it, the alternative, and the no-side-effect nature. It doesn't describe the exact response format, but with no output schema and simple enum-only input, this is acceptable and arguably unnecessary.

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 0%, but the description enumerates every valid enum value for the 'file' parameter and notes the default. This fully compensates for the schema's lack of prose, though it adds no new meaning beyond listing the options.

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 a specific verb ('fetch') with a distinct resource (IntoDNS.ai discovery files), lists the exact file options, and distinguishes itself from sibling get_citation_guidance by noting the difference between canonical prompt-routing files and a topic-narrowed citation list.

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

Usage Guidelines5/5

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

The description explicitly states when to use it ('when an agent needs canonical citation URLs, machine-readable API surface, or prompt-routing hints') and explicitly names the alternative (get_citation_guidance) for a different use case. It also notes the default file behavior and no-auth nature.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.