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

With no annotations and no output schema, the description carries the full burden of behavioral disclosure. It reveals the general output shape but does not state whether the operation is read-only, whether it has side effects, requires authentication, or has rate-limit or error behaviors. More transparency is expected for an unannotated tool.

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 concise sentences, front-loaded with the core purpose and output. Every sentence adds value, including the agent-vs-UI clarification. No redundant phrasing.

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 simple one-parameter tool, the description is mostly adequate, but the absence of an output schema and any behavioral caveats leaves gaps. An agent knows it gets a structured answer with certain categories but not the exact JSON shape or any usage limitations.

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 schema already fully documents the single parameter `q` as 'What you want to know' (100% coverage). The description adds the 'plain language' framing, which is useful but minimal. Baseline 3 is appropriate given high schema coverage.

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 uses a clear verb ('Ask') and resource ('Talon'), and specifies that it returns a structured answer with named categories. It implies a general-purpose natural-language query tool, though it does not explicitly distinguish itself from the large set of sibling tools.

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?

The phrase 'Ask Talon in plain language' implies when to use the tool, and 'Built for agents, not a UI' signals the intended caller. However, it gives no explicit exclusions or alternatives among the sibling tools, so the guidance remains implicit rather than direct.

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