adversarial_review

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

With no annotations, the description carries the disclosure burden. It reveals that the tool is adversarial, uses a different model family, and hunts for flaws, edge cases, security issues, and assumptions. This adds meaningful behavioral context beyond a generic 'review' statement, though it does not mention potential costs, rate limits, or output format.

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?

Two sentences with no waste. The first sentence states the core function, the second provides explicit usage guidance and behavioral detail. Very well structured and front-loaded.

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 description fully covers purpose, usage, and behavioral nuance for a tool with all-optional parameters and no output schema. It is complete for an agent to decide when to invoke it and what to expect.

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 each of the 5 parameters having a clear description. The tool description adds no additional parameter information, so it neither improves nor harms understanding. Baseline 3 is appropriate.

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 clearly states the tool's purpose with a specific verb ('Get'), a resource ('adversarial second opinion'), and a distinguishing detail (from Gemini Pro). It names concrete use cases (plan critiques, design reviews, pre-merge code review), which separates it from sibling tools like analyze_files or deep_search.

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 gives explicit when-to-use guidance: 'ALWAYS use this for plan critiques, design reviews, and pre-merge code review.' This clearly directs the agent for these scenarios and implicitly indicates other tools for other tasks.

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