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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds genuinely useful behavior beyond that: pasted notes are shown back 'shortened' with a structuring template, meaning raw input is never analyzed, and quotes are kept verbatim. That is real operational context an agent needs to set user expectations.

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?

Two sentences with the extraction outputs front-loaded and the important raw_transcripts caveat second, so an agent reads the primary behavior first. The output enumeration is dense but each item is a distinct deliverable; the only mild bloat is the parenthetical aside about shortening.

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 burden of describing results, and it does so by listing the extracted categories plus discovery questions and sector notes. It also disambiguates the two input paths (interview_notes vs raw_transcripts). The omission of any note about analysis_focus being inert is left to the schema, which covers it, so the definition is largely complete for a zero-required-param tool.

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 every parameter (including company, analysis_focus, product_category, and the nested interview_notes fields) is already documented in the schema itself. The description reinforces that analysis consumes structured interview_notes and that product_category drives sector notes, but adds little syntax or semantics beyond what the schema provides. 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 ('Extract') and a specific resource ('ICP patterns from customer interview notes'), then enumerates the exact artifacts produced (pain points, objections, buying triggers, value realized, champion roles, quotes, discovery questions, sector notes). The interview-notes resource is inherently distinct from siblings like icp_scoring_model or tam_sam_som_calculator, but no sibling is named, so it falls short of a 5.

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 implies usage by clarifying that 'only structured notes are analyzed' and that pasted transcripts are echoed back rather than processed, which is useful selection context. However, it never states when to reach for this tool versus the eight ICP siblings (deep dive, gap analysis, evolution tracker), leaving routing to inference.

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