logical_fallacy_detector

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

With no annotations, the description carries the full burden. It discloses the method ('pattern matching'), output format ('markdown report grouped by category with an overall severity assessment'), and per-fallacy details ('confidence score, description, before/after examples'). It does not mention limitations or false positives, but is otherwise transparent.

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?

Three sentences, no redundancy. First sentence states action and output details, second clarifies format, third gives usage guidance. 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?

Without an output schema, the description adequately explains the return value (markdown report with grouping and severity). Parameters are fully documented in the schema. The sibling mention provides context. Slightly more detail on limitations (e.g., not suitable for non-text inputs) would improve completeness.

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 no parameter-specific meaning beyond what the schema already provides. It mentions output elements (confidence, description, examples) but these are already implied by the parameters 'includeExamples' and 'includeExplanations'.

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 uses specific verbs ('detect and name') and resource ('logical fallacies in text'), and explicitly distinguishes itself from the sibling 'logical_argument_analyzer' by contrasting 'flag specific fallacies' vs 'full argument assessment'.

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?

Provides explicit guidance: 'Use this to flag specific fallacies; for a full argument assessment use logical_argument_analyzer.' This clearly states when to use the tool and when to use the sibling alternative.

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