MCP Cliniko 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. While 'Generate synthetic test data' implies a write operation (creation of data), the description doesn't specify whether this affects production data, requires special permissions, has side effects, or what the output looks like. For a tool that creates data with no annotation coverage, this lack of behavioral context is a significant gap.

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 directly states the tool's purpose without unnecessary words. It's appropriately sized for a simple tool and front-loaded with the core functionality. Every part of the sentence earns its place by specifying what, for whom, and the domain context.

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 creates synthetic data (a write operation) with no annotations and no output schema, the description is incomplete. It doesn't address critical context like whether this is for testing environments only, what data gets generated, authentication requirements, or potential impacts. For a data generation tool with zero structured behavioral information, the description should provide more operational guidance.

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 three parameters well-documented in the schema (num_patients, num_appointments, days_ahead). The description adds no additional parameter information beyond what's in the schema, so it doesn't enhance parameter understanding. According to the rules, with high schema coverage (>80%), the baseline score is 3 even without param info in the description.

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: 'Generate synthetic test data for Cliniko (Australian healthcare data)'. It specifies the verb ('Generate'), resource ('test data'), and domain context ('Cliniko', 'Australian healthcare data'), making the purpose unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'generate_comprehensive_test_data', which is a missed opportunity for 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. There's no mention of prerequisites, when this tool is appropriate, or how it differs from similar tools like 'generate_comprehensive_test_data' or 'cleanup_test_data'. Without this context, an agent might struggle to choose between these tools effectively.

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