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

Annotations already establish readOnly, idempotent, non-destructive, non-open-world, so the safety profile is covered. The description adds useful behavioral context (confidence L0, verbatim quote verification, PDF link per fact), but doesn't state result limits, pagination, or what happens when a section is absent.

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?

Front-loads what the tool returns and its section taxonomy, then verification semantics, then usage and param routing. The section list is long but each item is informative; only slight trimming possible.

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?

With no output schema, the description does the work of describing the returned fact shape (unit, condition, page, verbatim quote, confidence, PDF link), which is valuable. It also names where product_id comes from. The main gap is not distinguishing itself from sibling tools like get_component_specs.

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 coverage is 50% (only the 'q' param is described in schema). The description adds meaning by saying product_id can come from match_components or a product name, which compensates for the undocumented product_id. Baseline 3 given the mixed 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?

States a specific verb+resource ('Facts machine-read from a product datasheet, by section') and enumerates the sections covered, so an agent knows this retrieves structured datasheet extractions. It doesn't explicitly contrast with the sibling get_component_specs or search_datasheet_facts, which is the missing sibling differentiation.

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?

There is partial usage guidance: 'Use it for what the typed layer does not hold' and 'Pass product_id from match_components', which implies a workflow. But it never states when to prefer this over ask_datasheet or get_component_specs, nor when not to use it.

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