mcp-server-getalife

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

The description adds valuable behavioral context beyond what annotations provide. While annotations indicate read-only, non-destructive, idempotent, and closed-world behavior, the description reveals that the tool supports English and German, handles multiple transactions in one sentence, and returns confidence scores. This provides important implementation details not captured in annotations.

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 perfectly structured and concise. The first sentence states the core purpose, subsequent sentences provide specific examples and capabilities, and the final sentence explains the use case. Every sentence earns its place with no wasted words, and key information is front-loaded.

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's moderate complexity, rich annotations, and complete schema coverage, the description provides good contextual completeness. It explains the demonstration purpose, language support, multi-transaction handling, and confidence scores. The main gap is the lack of output schema, but the description compensates by mentioning what the tool returns (structured transactions with confidence scores).

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?

With 100% schema description coverage, the schema already documents both parameters thoroughly. The description mentions natural language input examples and currency support, but doesn't add significant meaning beyond what's in the schema descriptions. This meets the baseline expectation when schema coverage is complete.

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: it demonstrates how GetALife's AI voice input works by parsing natural language purchase descriptions into structured transactions with confidence scores. It specifies the verb ('demonstrates'), resource ('AI voice input'), and distinguishes from siblings by focusing on transaction parsing rather than budget analysis or financial planning.

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 clear context for when to use this tool: to show users how effortless expense tracking can be with voice input. It implies usage for demonstration purposes rather than actual transaction processing. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the sibling tools.

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