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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does state what the tool returns (markdown matrix with specific fields and partner sign-up links) and implies a read-only, non-mutating operation. However, it doesn't explicitly state there are no side effects, rate limits, or prerequisites. Given the tool's comparative nature, this is adequate but not exhaustive; a fully transparent description would explicitly confirm it performs no writes.

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 efficiently structured: it front-loads the core purpose, follows with the output specification, then usage guidance, and finally the sibling comparison. Every sentence earns its place, with no redundant or filler content. The example is illustrative without being verbose.

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 simplicity (single parameter, fully documented in schema) and the lack of an output schema, the description fully explains the return value in detail (markdown matrix fields and partner links). It also covers usage conditions and differentiates from the sibling. Nothing an agent needs to call it correctly is missing.

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 covers the only parameter ('tools') with a description specifying tool names and fuzzy matching. The tool description adds an example ('Apollo vs ZoomInfo vs Cognism vs Clay') and the 2–6 range (also in schema), but no new semantic meaning beyond the schema. Since schema coverage is 100%, the baseline of 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 opens with a clear, specific purpose: 'Side-by-side comparison of 2–6 GTM tools in one shot,' which names the verb, resource, and scope. It also lists the exact output fields (markdown matrix with cost, AI-readiness, etc.) and explicitly distinguishes itself from the 2-way sibling tool by name ('compare_tools'), so an agent can tell them apart immediately.

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 description gives explicit when-to-use guidance: 'Use for category bake-offs' with a concrete example, and then provides a clear exclusion criterion: 'Prefer the 2-way compare_tools for clean head-to-head pairs.' This directly tells the agent when to choose this tool over the named alternative, leaving nothing to inference.

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