analyze_cognitive_bias

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

No annotations are provided, so the description carries full burden. It mentions analyzing code/UI for cognitive bias across platforms, but lacks critical behavioral details: what the analysis outputs (e.g., findings, scores, recommendations), whether it's read-only or modifies input, any rate limits, or authentication needs. For a tool with 4 parameters and no output schema, this is a significant gap in transparency.

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 moderately concise with two paragraphs, but the first paragraph defines cognitive bias conceptually without directly stating the tool's action, which could be more front-loaded. The second paragraph specifies the analysis scope and platforms. Some redundancy exists (e.g., listing platforms when schema has enum), but overall it's structured adequately without excessive verbosity.

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 4 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., analysis results, error handling), behavioral constraints, or how it differs from sibling tools. For a cognitive analysis tool with multiple parameters, more context is needed to guide effective use.

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%, so the schema already documents all 4 parameters thoroughly with descriptions and an enum for 'platform'. The description adds no additional parameter semantics beyond implying platform flexibility ('CUALQUIER PLATAFORMA'), which is already covered in the schema. Baseline 3 is appropriate as the schema does the heavy lifting.

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 states the tool 'analiza código o componentes UI según esta ley' (analyzes code or UI components according to this law), which provides a general purpose. However, it's vague about what 'esta ley' (this law) specifically refers to (cognitive bias), and it doesn't clearly distinguish from siblings like 'analyze_cognitive_load' or 'analyze_working_memory' that also analyze cognitive aspects. The first paragraph defines cognitive bias but doesn't directly tie it to the tool's function.

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 mentions it works for 'CUALQUIER PLATAFORMA' (any platform) and lists examples, but provides no guidance on when to use this tool versus alternatives like 'ux_full_audit' or other analysis tools. There's no explicit when/when-not instructions or comparison to siblings, leaving the agent to infer usage based on the tool name alone.

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