timepiece_aggregate

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds detail on output format (markdown or JSON), which is valuable beyond annotations. No contradictions or missing critical behavioral traits.

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 well-structured with a clear title, purpose statement, and parameter list. It could be slightly more concise by removing redundant formatting, but it is reasonably efficient and front-loaded.

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 complexity of aggregation across multiple issues and the presence of an output schema, the description covers all necessary aspects: purpose, parameters, return format, and aggregation types. No critical gaps.

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 schema description coverage at 0%, the description fully compensates by listing all parameters with types, defaults, and brief explanations. This adds essential meaning that the schema alone lacks, making parameter semantics clear.

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 specific verb 'aggregate' and resource 'time-in-status statistics across multiple Jira issues'. It distinguishes from siblings like timepiece_get_issue (single issue) and timepiece_list_issues (listing), making purpose unambiguous.

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 statistical aggregation across issues matching a JQL query. While it doesn't explicitly state when not to use alternatives, the purpose is clear enough that an agent can infer appropriate context given sibling tool names.

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