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

Beyond the readOnlyHint annotation, the description discloses significant behavioral details: the response contains 'when to use it, what it refuses, a working example, effective access limits, important outputs, provenance fields, recommended next calls, and the shared natural-language-to-strict-JSON interaction contract.' This goes beyond the annotation and gives the agent a full picture of the tool's behavior and output breadth. No contradictions detected.

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

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

The description is two sentences, front-loaded with the core purpose. The second sentence, while listing many return items, is a single efficient list that avoids redundancy. Every sentence earns its place—there is no filler or repeated schema information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a meta-tool with one parameter and no output schema, the description is complete: it explains what the tool does, what it returns, and how to invoke it in a workflow. It covers usage context and expected content, leaving no significant gaps for an agent to guess.

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

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

The input schema already describes the sole parameter 'tool_name' as 'Exact tool name from tools/list,' so schema coverage is 100%. The description reinforces this by mentioning 'Use tools/list to discover names' but adds no new semantic information about the parameter beyond what the schema provides. Baseline 3 is appropriate.

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

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

The description clearly states the tool's purpose: 'Free blind-caller guidance for one tool visible on this MCP facade.' It uses a specific verb ('guidance') and resource ('one tool'), and distinguishes itself from sibling data-access tools like get_catalog and query_dataset by being a meta-help tool. The list of returned content (when to use, what it refuses, etc.) further clarifies its unique role.

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

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

Explicit guidance is provided: 'Use tools/list to discover names, then call this before an unfamiliar tool.' This gives a clear workflow, specifies when to use the tool, and implicitly names the alternative (tools/list) for discovery. It also indicates the tool should be used proactively for unknown tools, leaving no ambiguity.

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