compare_review_intelligence

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

With no annotations, the description carries the full burden but only lists output content. It does not disclose whether the operation is read-only, any required permissions, or potential error conditions (e.g., firms without sufficient review data). This is a moderate disclosure level, enough to understand the result but not the full behavioral context.

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 a single, information-dense sentence. It front-loads the action (Compare) and resource (review intelligence) and then lists the return dimensions without wasted words.

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 sufficiently explains what the tool returns, covering the main output aspects. Given there is no output schema, this is important. However, it omits any edge-case behavior or prerequisites (e.g., how many reviews a firm needs), leaving a minor 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?

The sole parameter firm_slugs is well-documented in the schema (array of 2-5 strings). The description adds no extra semantics beyond what the schema already provides, so the baseline score of 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 function: comparing AI-analyzed review intelligence across 2-5 law firms. It lists specific output dimensions (pain points, sentiment, trust signals, etc.), distinguishing it from sibling tools like get_review_intelligence (single firm) and compare_attorneys (attorney-centric).

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 implies usage for competitive analysis and specifies the input range (2-5 firms), providing clear context. However, it does not explicitly mention when not to use this tool or name alternatives, so it falls short of a 5.

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