adversarial_review

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

With no annotations, the description carries the behavioral burden. It reveals the tool uses a different model family, hunts for flaws, edge cases, security issues, and unstated assumptions, which gives a clear sense of its adversarial nature. It doesn't detail side effects or performance, but the core behavior is well disclosed.

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, no fluff. The first sentence defines the tool; the second gives explicit usage directives. Every word earns its place, and the key information is 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?

Given the tool's moderate complexity (5 optional params, no output schema), the description provides sufficient context for selection and invocation. It covers what the tool does, when to use it, and the schema handles parameters. It doesn't explain return format, but that's not critical for this review-style tool.

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?

The input schema has 100% coverage with descriptive parameter docs. The tool description itself does not add parameter-level semantics, so the baseline of 3 applies. The schema already explains each parameter adequately.

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 provides an adversarial second opinion from a different model family (Gemini Pro), and explicitly lists concrete use cases (plan critiques, design reviews, pre-merge code review). This distinguishes it from sibling tools like analyze_files or deep_search, which serve different purposes.

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?

Explicitly states 'ALWAYS use this for' the listed review scenarios, giving clear when-to-use guidance. It does not explicitly mention when not to use it or name alternatives, but the strong directive and adversarial framing effectively guide selection.

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