analyze_sprint_health

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

With no annotations, the description carries full responsibility for behavioral disclosure. It fails to mention that this is a read-only analysis, whether it makes external calls, what specific metrics are computed, or what the output structure looks like. The 'AI-powered' wording hints at complexity but leaves the operational behavior opaque.

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, compact sentence that front-loads the core purpose. It avoids excessive detail and is easy to parse. Slightly more specificity would be useful, but it is appropriately sized.

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?

For a tool that purportedly performs AI-driven analysis, the description is notably incomplete. It does not specify what metrics are analyzed, what kind of recommendations are generated, whether the result is a report or a visual, or any dependent data requirements. The absence of an output schema or annotations increases the need for descriptive completeness, which is lacking.

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?

Both parameters (sprintId and boardId) have descriptive schema entries, achieving 100% schema coverage. The description adds no additional parameter context beyond this, so the baseline score of 3 is appropriate.

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 analyzes sprint health and produces metrics and recommendations. It uses a specific verb ('analyze') and resource ('sprint health'), distinguishing it from sibling tools that deal with raw sprint data or issue management. However, 'AI-powered' is somewhat vague and doesn't fully define what health means.

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 no guidance on when to use this tool versus alternatives like get_sprints or get_sprint_issues. There is no mention of use cases, prerequisites, or exclusions. The agent must infer usage solely from the tool name and sibling context.

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