nativ-mcp

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

No annotations are provided, so the description carries the full burden. It describes the tool as a search function, implying it's read-only and non-destructive, which is adequate for basic transparency. However, it lacks details on behavioral traits like rate limits, authentication needs, error handling, or how results are returned (e.g., format, pagination), leaving gaps in understanding the tool's operation.

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 well-structured and appropriately sized. It starts with a clear purpose sentence, followed by usage guidelines, and then a parameter section with concise explanations. Every sentence adds value without redundancy, and the information is front-loaded for quick understanding.

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 5 parameters with 0% schema coverage and an output schema present, the description does a good job of compensating. It explains all parameters thoroughly and provides usage context. The output schema likely covers return values, so the description doesn't need to detail them. However, it could improve by mentioning sibling tools for better integration, but overall, it's quite complete for a search tool.

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 0%, so the description must fully compensate. It provides detailed semantics for all 5 parameters: explains 'query' as text to search, 'source_language_code' with default, 'target_language_code' as optional filter, 'min_score' as fuzzy match range, and 'limit' as result maximum. This adds significant meaning beyond the bare schema, making parameters clear and actionable.

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: 'Search the translation memory for existing translations.' It specifies the verb ('search') and resource ('translation memory'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'get_translation_memory_stats' or 'translate', which could help avoid confusion.

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 usage context: 'Use this to check if translations already exist before creating new ones, or to find reference translations for consistency.' This gives practical scenarios for when to use the tool. It doesn't explicitly state when not to use it or name alternatives among siblings, but the guidance is helpful for typical use cases.

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