Tally MCP Server

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 mentions the tool validates logic to prevent errors, which implies a read-only, non-destructive operation, but doesn't specify what happens during validation (e.g., returns errors, warnings, or a pass/fail result), any rate limits, or authentication requirements. For a validation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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, efficient sentence that front-loads the core purpose and includes a specific example of common errors. There is no wasted text, and it directly communicates the tool's function without unnecessary elaboration.

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 complexity (2 parameters with nested objects, no output schema, and no annotations), the description is adequate but incomplete. It explains what the tool does but lacks details on validation outcomes, error handling, or usage context relative to siblings. For a validation tool with structured inputs, more behavioral context would enhance 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 schema already documents both parameters ('triggerQuestion' and 'conditionalLogic') with descriptions. The description adds minimal value beyond the schema by hinting at validation rules (e.g., preventing 'equals' vs 'contains' errors), but doesn't provide additional syntax, format details, or examples. Baseline 3 is appropriate when 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 clearly states the tool's purpose: 'Validate conditional logic for multiple choice questions' with a specific goal to 'prevent common errors like using "equals" instead of "contains"'. It uses a specific verb ('validate') and resource ('conditional logic for multiple choice questions'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'validate_form_logic_flow', which appears related.

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 by specifying 'multiple choice questions' and 'conditional logic', suggesting it should be used when validating such logic. However, it lacks explicit guidance on when to use this tool versus alternatives like 'validate_form_logic_flow' or other sibling tools, and doesn't mention prerequisites or exclusions.

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