Suggest ai tracking prompts

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

Annotations already declare readOnlyHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description still adds real value beyond that: no model generation, no prompt persistence, no paid provider calls, and the important caveat that returned templates are unranked heuristics with no measured popularity.

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?

Three tight sentences, front-loaded with what it reads before the output caveat and the negative disambiguation. Slightly cryptic phrasing ('for explicit review') costs it the top score, but there is no filler.

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 no output schema, the description carries the return-value burden and does characterize the output as manual, heuristic templates without measured popularity. Combined with annotations covering safety and a fully documented single parameter, the definition is close to complete, though the missing link to the sibling suggestion/generate tools leaves a routing 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 description coverage is 100% and the single project_id parameter is fully documented in the schema, including the ID pattern and the membership/token-scope enforcement note. The description adds no additional meaning about the parameter, so the baseline 3 applies.

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 never plainly states that the tool returns suggested AI-tracking prompts; the purpose is only inferable from the title plus the oblique phrase 'Returned manual templates are heuristics.' It does convey the inputs (project context and authoritative competitors), but an agent has to assemble the verb+resource from the name rather than the text.

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?

Usage is implied through contrast ('never generates with a model, saves a prompt or starts paid provider work') and the phrase 'for explicit review,' which hints this is the zero-cost, non-committal option. However, it never names the alternatives it is contrasted against (ai_tracking_suggestions_generate, ai_tracking_suggestions_preview, accept_ai_tracking_suggestions) or states the condition that should select this one.

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