get_architecture_impact

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

With no annotations, the description carries the full burden. It does disclose the analysis nature ('identify', 'assess') and details the return structure, which is useful. However, it omits any mention of authentication, rate limits, or side effects, though the tool appears to be a read-only query. It adds some context but not rich behavioral detail.

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 concise and front-loaded with the main purpose. However, the first sentence lists three contribution types that are immediately repeated in the bullet list with the full set of seven, creating minor redundancy. Overall, it is efficiently structured.

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?

The description adequately captures the tool's core functionality and return values, complementing the rich input schema and output schema. It lacks comparisons to sibling tools and notes on permissions or limitations, but for an analysis tool this is a minor gap.

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%, so the baseline is 3. The description does not add meaning beyond the schema's parameter descriptions (e.g., repo filter, date range), but the schema itself is clear and self-sufficient.

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 tool's specific function: identifying contribution types and assessing their impact on codebase health. It lists detailed output fields (classification, impact level, health delta, complexity, first principles) that distinguish it from generic analytics tools like get_contribution_metrics.

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 offers no explicit guidance on when to use this tool versus its siblings (e.g., get_contribution_metrics, scan_first_principles). It only describes the output without mentioning alternatives, exclusions, or typical use cases, leaving the agent to infer.

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