analyze_feedback_by_group

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

With no annotations, the description carries the full burden. It discloses the read-only nature implicitly via 'Analyze and group' and specifies return values, but it does not explicitly state non-destructiveness, permissions, pagination, or edge cases like empty groups. This is moderate transparency, not minimal.

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 two sentences, front-loaded with the action and outputs, and includes relevant examples. Every part contributes to understanding the tool without unnecessary detail.

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?

The tool is relatively simple with two params and no output schema. The description covers the return shape ('counts, total votes, and aggregated MRR') and use cases. Minor gaps exist around pagination and exact aggregation behavior, but the essential context is present.

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 coverage is 100% with good descriptions for both parameters (group_by enum and project_id with usage note). The description reinforces group_by but adds little beyond the schema. Baseline 3 is appropriate when the schema handles the meaning well.

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 ('Analyze and group'), a clear resource ('all feature requests'), a defined dimension ('status or priority'), and states the outputs ('counts, total votes, and aggregated MRR'). This distinguishes it from siblings like list_feature_requests (which lists) and get_project_stats (which provides stats without grouping).

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 clear usage context with examples ('Ideal for generating summaries like...') and the schema adds guidance for project_id (use list_projects when multiple projects). It does not explicitly state when not to use this tool or name alternatives, but the context is strong.

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