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

The description discloses critical behavioral traits: it is fully deterministic ('no model call'), reproducible, costs $0.03 per call, and returns a clean/review/fail verdict. It also notes that patterns requiring full user flow are identified. However, it does not mention any limitations such as static-only analysis or error handling, which are not covered by annotations (none provided).

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 paragraph that front-loads the main purpose and efficiently covers key details like determinism, cost, and verdict. It is slightly verbose but every sentence adds value.

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 lack of an output schema and the tool's moderate complexity, the description covers essential aspects: input sources, output (patterns with evidence/regulation/alternative), verdict, and cost. It mentions needing full user flow for some patterns. However, it does not describe error conditions or the exact format of returned data.

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 baseline is 3. The description adds context by explaining the verdict system and the overall function, but it does not enhance the understanding of individual parameters beyond what the schema already provides.

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: 'Scan a live page or raw HTML for deceptive design.' It specifies the action (scan), the resource (page/HTML), and the outcome (detect deceptive patterns with evidence, regulation, and alternative). This distinguishes it well from siblings like 'psych_biases' or 'content_ai-score'.

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 context through features like deterministic results and cost, but it does not explicitly state when to use this tool versus its sibling 'psych_dark-patterns' or other alternatives. It mentions verdicts suitable for deployment gating but lacks direct guidance on when not to use it.

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