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

With no annotations, the description carries the transparency burden. It discloses that absence is intentional and lists specific recorded reasons (vendor states outright, official pages contradict, allowance changes, no official page). This gives the agent insight into returned explanations, though it doesn't specify the response format.

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?

Two sentences, no filler. Front-loaded with purpose, then provides essential behavioral context. Every sentence earns its place.

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?

Given the tool's low complexity and complete parameter schema, the description covers the main use cases. It doesn't state what happens for an unknown tool or the exact output format, but the explanation kinds are listed, making it sufficient for an AI agent to understand the tool's role.

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?

Schema description coverage is 100%, so the baseline is 3. The description adds context about tool omission (in the tool schema) and the reason categories, but doesn't add meaning beyond the schema's parameter descriptions. The tool's purpose is reinforced, but parameter semantics are adequately covered by the schema.

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: 'Explain why this dataset publishes no figure for a given tool.' It uses a specific verb ('explain') and identifies the resource ('this dataset' and 'a given tool'), distinguishing it from sibling tools that retrieve limits or alternatives.

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?

Explicitly states when to use: 'Use this when a user asks why you cannot give them a number, or when they cite a figure you cannot source.' It also frames absence as 'a finding, not an oversight,' providing context that prevents misuse.

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