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

Goes well beyond the readOnly/idempotent annotations: it explains the NOT_COVERED semantics (absence of scoring ≠ no fit), the free-tier truncation behavior (first 5 rows, locked.count/by_type), and the permanent withholding of contact values and decision-maker names, plus the entitlement/locked response fields. This is exactly the behavioral context annotations cannot convey.

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-loaded with the core purpose and the important NOT_COVERED caveat, then the access rules. Dense but each clause carries real information; the trailing plan promotion and URL are the only slightly wasteful element.

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 carries the return-shape burden and does so: it lists the match fields returned and describes the entitlement/locked envelope for gated responses. Nothing an agent needs to call and interpret this tool 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?

Schema coverage is 50%: dfx_id is documented in both schema and description (dfx:pe:<uuid> format), but the limit parameter is only defined by schema bounds/default. The description adds no syntax or format meaning beyond what the schema already carries, so baseline 3 applies.

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: computed company_for_buyer matches for one PE firm, enumerating the returned fields (reasons, blockers, why_now, comparables, score, confidence, date). The direction (firm → companies) is unambiguous, though it never names the reverse sibling find_pe_buyers_for_company to sharpen the distinction.

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?

Usage is implied by the required dfx:pe: input and by the NOT_COVERED caveat, which tells the agent the empty-result case is meaningful. There is no explicit when-to-use-this-vs-an-alternative guidance, so the agent must infer routing from the tool name alone.

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