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

No annotations are provided, so the description bears the full burden. It reveals what the tool returns (fit scores, cost ranges, evidence URLs, etc.) and notes API parity via 'Same input as POST /api/v1/recommend'. It does not explicitly confirm the non-mutating nature of the operation or any external dependencies, but 'Recommend' strongly implies a read-only analysis.

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 a single sentence that front-loads the core purpose, lists the key output components, and adds the API parity hint. Every part earns its place with no redundant wording.

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?

The presence of an output schema covers the return value structure, and the description covers the high-level recommendation task. But with four parameters and sibling tools available, the description lacks guidance on when to choose this over related tools and provides almost no parameter semantics, leaving the agent to infer important invocation details from names and the schema alone.

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 only 25%, so the description must compensate for the undocumented parameters. It does not explain budget_usd, requires_login_session, or team_maintenance_capability, and only loosely implies that 'workload' is the main input. The reference to the API endpoint is a helpful pointer but not self-contained parameter guidance.

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 action ('Recommend'), the deliverable ('an architecture and up to three providers'), the input ('for a workload'), and the contents of the result ('fit scores, cost ranges, reasons, limitations, assumptions and evidence URLs'). This distinguishes it from siblings like estimate_cost or compare_products, which focus on narrower tasks.

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 'for a workload' establishes a clear usage context: agents should call this when they need a full recommendation rather than a single cost estimate or provider comparison. However, it does not explicitly mention alternatives or state when not to use it, so some inference is required.

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