booboo_count

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

No annotations are present, so the description carries the full burden. It clearly explains the aggregate-filter-group-count behavior and gives concrete examples showing `where`, `since`, `groupBy` and `type` usage. It does not explicitly state read-only/reversibility, but the 'count' semantics make side effects unlikely.

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 behavior and includes two concrete JSON examples that occupy most of the text. Each sentence earns its place, though the inline examples make it a bit dense; still clearly organized.

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 9-parameter tool with no output schema and no annotations, the description provides enough context for the primary use cases and even shows full request examples. It does not describe the return shape or all optional parameters, but the purpose and common syntax are well covered.

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 description coverage is 67%, and the description adds value by demonstrating how parameters combine in real examples (e.g., `where` with dotted data paths, `since` with ISO dates, `groupBy` with data.subject). It also gives meaning to the otherwise undocumented `type` parameter through the example `type:'observation'`, though `layer` and `cluster` remain unexplained.

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 uses a specific verb ('Aggregate: filter the graph, then group and count') and explicitly contrasts with booboo_search: 'search ranks, this counts.' This makes the tool's function and scope clear and distinguishes it from sibling tools.

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?

It provides explicit usage criteria: 'Use for how many, top N, most/least and any date-window question' and names the alternative ('search ranks, this counts'). This is direct when-to-use guidance with a clear exclusion.

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