aiworkhub_manager_recipe_usage

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

Goes well beyond the readOnlyHint annotation: never-run recipes are included with used=false rather than omitted, actors are server-derived from the verified route so counts cannot be inflated, and pre-actor runs surface as unattributed_runs. The remaining gap is output behavior around limit/truncation, which is not addressed.

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?

Front-loaded with the core answer and organized into scoping, provenance, and parameter paragraphs. Slightly verbose in places (the 'actionable state' rationale), but nearly every sentence carries distinct 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?

With an output schema present, the description needn't enumerate return fields, yet it still explains the notable ones (exit-code distribution, bytes, distinct_actors). Only the pagination/limit dimension is left uncovered for a tool that defaults to 100 rows.

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 0%, so the description must compensate. It fully explains `since` (ISO-8601 UTC bound on the evidence window, with registered_count and window_only describing the asymmetry) but says nothing about `limit`, including what truncation means for a partial result set.

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?

Opens with a specific verb-and-resource statement: 'which registered recipes are actually used, and by whom.' It explicitly contrasts with aiworkhub_manager_recipe_list ('answers how many recipes EXIST'), so an agent can distinguish the two without opening either schema.

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?

Names the alternative sibling directly and states the exact condition that selects it: existence-count questions go to recipe_list, usage questions come here. It also signals the tool is for manager-read analysis, not mutation.

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