get_ai_insights

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

Annotations indicate readOnlyHint=true, so the read-only nature is covered. The description adds no further behavioral context such as data freshness, rate limits, or potential side effects. For a tool with only annotation-level disclosure, the description does not supplement beyond listing output categories.

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 a single sentence that front-loads the core purpose and lists analytics components efficiently. It is not overly verbose, though it could be slightly restructured for readability. It earns its place with specific, actionable information.

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 has one parameter, no output schema, and readOnlyHint annotation, the description covers the data types returned. However, it does not detail the output structure or format. While it lists analytics categories, an agent might need more clarity on how to interpret the response.

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 100%, with the range parameter fully described via enum and pattern. The description does not add any additional meaning about the parameter (e.g., format or usage tips). Baseline score of 3 is appropriate as schema already carries full burden.

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 explicitly states 'Get AI-assisted coding analytics' and lists five specific analytics categories (adoption timeline, contribution share, comparison by language, project-level dependency, efficiency trends). This clearly distinguishes it from siblings like get_developer_context or get_productivity_summary.

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 for AI analytics queries but does not explicitly state when to use this tool versus alternatives, nor does it provide exclusion criteria or prerequisites. Context signals show three sibling tools, but no comparative guidance is offered.

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