fleet_review

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

With no annotations, the description carries the full burden. It discloses key behaviors: parallel execution, side-by-side response formatting, and default agents (codex + agy). While it doesn't discuss error handling or costs, these are not essential for selecting this tool for its intended review use case.

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 long, front-loads the action, and contains no redundant words. Every phrase advances understanding: the behavior, use cases, and defaults are all packed efficiently.

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 tool with a simple signature and fully described schema, the description delivers purpose, usage guidance, and defaults, which is sufficient. The output format is summarized as 'side by side,' and no output schema exists, so no further detail is required. It is complete enough for an agent to decide when and how to use it.

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?

Input schema covers all 4 parameters with descriptions and defaults (100% coverage), so baseline is 3. The description adds minimal extra meaning—reiterating defaults and providing example prompts—but does not significantly enrich parameter understanding beyond the schema.

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 and resource: 'Fan out the same prompt... to multiple agents in parallel and return all responses side by side.' It clearly differentiates from siblings like fleet_run and fleet_status by focusing on parallel agent review, making the tool's purpose unmistakable.

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 explicit use cases: 'Use for consensus code review or to get diverse model perspectives before deciding.' It gives clear context but stops short of specifying when not to use it or naming alternative tools explicitly, so it earns a 4 rather than a 5.

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