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

Annotations already declare readOnlyHint, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuinely new behavioral guarantees beyond that: no invented facts about the competitor ('every line comes from your inputs and the sector') and an ethical constraint ('without negative selling'). It does not discuss output length or formatting, but the core behavioral promise is unusually well stated.

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?

Three sentences, front-loaded with the value proposition, then inputs, then outputs. Dense but every clause carries information; the final sentence about not inventing competitor facts is the most valuable and is placed last, which slightly buries it. No filler or repetition.

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 10 parameters and no output schema, the description compensates by enumerating the returned components (set up, discovery questions, criteria, reference call questions, requirement and scenario traps, commercial terms, tactics, sector notes). The schema also fully documents parameters and enums. Remaining gap is output structure or volume, which an agent would still have to discover by calling.

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 100%, so the baseline is 3. The description reinforces the meaning of competitor, your_solution, your_strengths, and competitor_weaknesses as user-supplied rather than inferred, but it says nothing about trap_type, evaluation_stage, buyer_persona, or business_model beyond what the schema already documents. It adds emphasis rather than new semantics.

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 a specific verb and resource: it decides which questions expose gaps in a named competitor and returns a defined set of positioning artifacts. It implicitly separates itself from generic siblings like discovery_question_bank by naming competitor-specific outputs (requirement and scenario traps, commercial terms). It stops short of naming a sibling or an explicit exclusion, so it is clear but not fully differentiated.

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?

It describes what inputs to supply ('the named competitor, your solution, your strengths and its weak points') and the constraint 'without negative selling', which implies a pre-deal competitive positioning context. There is no explicit when-to-use versus deal_strategy_coach, discovery_question_bank, or win_loss_analyzer, and no stated preconditions such as needing a known competitor already selected.

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