DesktopInsights

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

Annotations already indicate read-only, non-destructive, and open-world hints, but the description adds valuable context beyond this by specifying the scope (e.g., returns full technology stack with 7+ SDK categories, detailed dependency lists with versions, and coverage of 12,000+ apps), enhancing the agent's understanding of what data to expect without contradicting annotations.

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 front-loaded with the core purpose in the first sentence, followed by supporting details (e.g., return content, input examples, coverage), with no wasted words; every sentence adds value, making it efficient and well-structured for quick comprehension.

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 the tool's moderate complexity, rich annotations, and no output schema, the description is mostly complete by detailing return values (technology stack, dependency lists) and input scope. However, it could slightly improve by mentioning potential limitations or error cases, though it adequately supports agent usage.

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?

With 100% schema description coverage, the input schema already fully documents the parameters ('app' and 'platform'). The description adds minimal extra semantics by mentioning examples like 'Figma' or 'Slack' and bundle IDs, but does not provide significant additional meaning beyond what the schema offers, meeting the baseline for high coverage.

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 clearly states the specific action ('Look up') and resource ('SDKs, frameworks, and dependencies a specific desktop application uses'), distinguishing it from siblings like 'compare_apps' or 'search_apps' by focusing on detailed technology stack retrieval rather than comparison or general search.

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 provides clear context for when to use this tool (e.g., for retrieving technology stacks of desktop apps) and mentions coverage of 12,000+ macOS and Windows apps, but does not explicitly state when not to use it or name alternatives like 'compare_apps' or 'search_apps' for different scenarios.

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