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

Annotations already cover the safety profile (readOnly, non-destructive, closed-world), so the description's job is to add context, and it does: it enumerates what comes back (a candidate change per input, a draft updated ICP, unnamed roles, loss reasons to tag, CRM pulls) and discloses the win-rate limitation. What it omits is any note on how candidates are derived or how much of the answer is generic versus input-driven.

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 decision the tool supports, then inputs, then outputs, then the limitation. The middle output list is dense but each item is a distinct deliverable, so little padding is present.

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?

There is no output schema, and the description usefully compensates by enumerating the returned artifacts, which is the main completeness risk for this tool. With seven params all documented in the schema, the remaining gap is minor: no guidance on how detailed the input strings should be for good results.

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 restates the four core inputs (current ICP, recent wins, recent losses, market changes) but says nothing about the optional company, product_category, or time_period fields, so it adds no meaning beyond the schema.

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 opens with a specific verb and outcome: 'Helps you decide whether your ICP should change after recent wins and losses.' That distinguishes it from siblings like icp_scoring_model or tam_sam_som_calculator, though it never explicitly names an alternative such as icp_gap_analysis, so the differentiation is inferential rather than stated.

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 trigger context is clear ('after recent wins and losses'), and the closing line sets a boundary: 'It does not compute win rates; check each candidate against your CRM.' That tells the agent what this tool will not do, but it stops short of routing to a specific sibling for the quantitative side.

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