analyze_similarity_law

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool 'analiza' (analyzes), implying a read-only operation, but doesn't clarify output format, potential side effects, error handling, or performance considerations. For a tool with 4 parameters and no output schema, this leaves significant behavioral gaps, though it doesn't contradict any annotations.

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 appropriately sized and front-loaded, starting with the law's definition and immediately stating the tool's function. The two sentences are efficient, with no redundant information. However, the inclusion of an emoji (🔍) and the law's name in Spanish adds minor stylistic elements that don't enhance clarity, slightly reducing conciseness.

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 complexity (analyzing UX laws across multiple platforms with 4 parameters) and lack of annotations and output schema, the description is incomplete. It doesn't explain what the analysis entails, what results to expect, or how to interpret outputs. For a tool with no structured behavioral hints, this leaves the agent under-informed about its operation and outcomes.

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 description coverage is 100%, with all parameters well-documented in the schema (e.g., 'code' as UI component code, 'platform' with enum values). The description adds minimal value beyond this, only implying analysis of 'código o componentes UI' which loosely maps to the 'code' and 'component_description' parameters. Since the schema does the heavy lifting, 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 purpose: analyzing code or UI components according to the Law of Similarity for any platform. It specifies the verb 'analiza' (analyzes) and the resource 'código o componentes UI' (code or UI components), making the action concrete. However, it doesn't explicitly differentiate from sibling tools like 'analyze_proximity_law' or 'analyze_common_region_law', which likely analyze other Gestalt principles, so it misses full sibling distinction.

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 no guidance on when to use this tool versus alternatives. It mentions applicability to 'CUALQUIER PLATAFORMA' (any platform), but doesn't specify scenarios, prerequisites, or exclusions. With many sibling tools analyzing different UX laws (e.g., 'analyze_fitts_law', 'analyze_hicks_law'), the lack of comparative context leaves the agent without clear usage criteria.

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