VidLens

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

Strong behavioral disclosure given zero annotations: includes performance characteristics '[~30-60s, vision comparison]' and return type 'image-backed matches'. However, does not disclose state changes (what dryRun prevents) or failure modes.

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?

Optimal density: opening clause establishes purpose/technology, second clause covers input/output modalities, bracketed suffix provides performance metadata. Zero redundant words.

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 6 parameters (50% schema coverage) and no output schema, description covers core functionality and timing but omits return structure details and the three undocumented parameters' semantics. Minimum viable for a CV tool of this complexity.

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 coverage is 50% (3 undocumented: maxResults, minSimilarity, dryRun). Description adds critical semantic value by clarifying assetId and framePath are mutually exclusive alternatives (XOR), but does not compensate for the three undocumented parameters.

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?

Excellent specificity: 'Find frames' (verb) + 'using Apple Vision image feature prints' (method/resource). Clearly distinguishes from text-based sibling 'searchVisualContent' and extraction tool 'extractKeyframes' by emphasizing visual similarity matching.

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?

Provides implied usage guidance by describing the two alternative input methods (assetId OR framePath), but lacks explicit when-to-use guidance versus 'searchVisualContent' or prerequisites like whether frames must be indexed first.

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