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

Beyond the readOnlyHint, idempotentHint, and non-destructive annotations, the description adds meaningful behavior: the matches are computed, the matcher fields are returned verbatim, and NOT_COVERED is explicitly explained as meaning the matcher scored nothing, not that no add-on fits. This is valuable context that annotations do not provide and prevents misinterpretation of empty or sparse results.

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 compact and front-loaded: the core purpose is stated first, followed by the output contents and the critical NOT_COVERED caveat. There is no filler or redundancy, and every sentence adds useful information.

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 that there is no output schema, the description does a strong job of enumerating the returned fields and explaining the one tricky result state (NOT_COVERED). It also identifies the required input and its source. For a read-only computed lookup, this is complete enough for an agent to select and call the tool correctly.

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 description adds useful meaning to dfx_id by specifying it is a platform company id from search_pe_platforms. However, the optional limit parameter is not described beyond its schema default/min/max, and schema coverage is only 50%. The description partially compensates but does not fully explain both parameters.

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 states exactly what the tool does: it returns computed add-on matches for a single platform company, listing the candidate, matcher's reasons, blockers, why_now, comparable add-ons, owner, score, confidence, and computed date. It also names the expected input source (a dfx:pe: company id from search_pe_platforms), which distinguishes it clearly from sibling tools that handle buyers, firms, or funds.

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 clear usage context: use it for one platform company identified by a dfx:pe: id from search_pe_platforms. It does not explicitly enumerate alternatives or exclusions, but the input source and singular-platform scope make the intended use reasonably obvious. The NOT_COVERED caveat also helps the agent interpret empty results correctly.

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