vidlens-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's outputs (e.g., momentum signals, saturation analysis) and data source ('YouTube search data'), and acknowledges limitations ('honest limitations disclosed'). However, it does not detail aspects like rate limits, authentication needs, or error handling, leaving some behavioral traits unspecified.

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 front-loaded with the core purpose in the first sentence, followed by specific outputs and context. Every sentence adds value without redundancy, making it efficiently structured and appropriately sized for the tool's complexity.

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 complexity (5 parameters, no output schema, no annotations), the description provides a good overview of purpose and outputs, but lacks details on parameter usage and behavioral constraints. It is complete enough for initial understanding but could benefit from more guidance on when and how to use the tool effectively.

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 40% (2 out of 5 parameters have descriptions: 'niche' and 'regionCode'). The description does not add specific meaning to parameters beyond what the schema provides, such as explaining 'dryRun' or 'lookbackDays' effects. With low coverage, the description does not fully compensate, but the baseline is adjusted due to the schema's partial documentation.

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: 'Discover what's trending in a niche right now' with specific outputs like 'top-performing and recent videos, momentum signals, saturation analysis, content gap opportunities, keyword patterns, and format breakdown.' It distinguishes itself from siblings like 'exploreNicheCompetitors' or 'researchTagsAndTitles' by focusing on trend discovery rather than competitor analysis or tag research.

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 for trend discovery in a niche, but does not explicitly state when to use this tool versus alternatives like 'exploreNicheCompetitors' or 'researchTagsAndTitles.' It mentions being 'grounded in YouTube search data,' which provides some context, but lacks clear exclusions or comparisons to sibling tools.

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