Linkly MCP Server

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

No annotations are provided, so the description carries full burden. It mentions 'click counts' and 'grouped by a dimension' but lacks behavioral details like whether this is a read-only operation, if it requires authentication, rate limits, pagination, or what the output format looks like. For an analytics tool with 8 parameters, this is a significant gap in transparency.

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 two concise sentences with zero waste: the first states the core functionality, and the second provides usage context. It's front-loaded with the main purpose and efficiently structured.

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 (8 parameters, no annotations, no output schema), the description is incomplete. It doesn't explain the return values (e.g., format of grouped data), behavioral aspects like error handling, or how it differs from sibling tools. For a data retrieval tool with multiple filters, more context is needed to guide effective use.

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 all parameters thoroughly. The description adds minimal value beyond the schema by listing example dimensions (country, platform, browser, etc.), but doesn't provide additional semantics like how grouping works or interactions between parameters. Baseline 3 is appropriate when 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: 'Get click counts grouped by a dimension' with examples like country, platform, browser. It specifies the verb ('Get') and resource ('click counts'), but doesn't explicitly differentiate from sibling tools like 'get_analytics' or 'get_clicks', which likely provide different analytics views.

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 implied usage context: 'Useful for breakdowns and top-N reports.' This suggests when to use it, but doesn't explicitly state when not to use it or name alternatives among siblings (e.g., 'get_analytics' might be for aggregated totals). No clear exclusions or prerequisites are mentioned.

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