Statonic 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 describes the action (analyze video, extract hook formula/text, append to JSON file) and the purpose (build knowledge base), but lacks details on permissions needed, rate limits, error handling, or what 'hook formula' entails. It doesn't contradict annotations, but could provide more operational context.

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 efficiently structured in two sentences: the first states the core functionality, and the second provides usage guidance. Every sentence adds value without redundancy, making it appropriately sized and 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 complexity (analyzing video content and updating a knowledge base), no annotations, and no output schema, the description is minimally adequate. It explains the purpose and outcome, but lacks details on behavioral traits, error cases, or output format, leaving gaps for an AI agent to infer.

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?

The input schema has 100% description coverage for its single parameter ('video_path'), so the baseline is 3. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., no format constraints or examples for 'video_path'), but it doesn't need to compensate for gaps.

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: 'Analyze a trending video file to extract its hook formula and text. Appends the learned example to hook-knowledge.json for future use.' It specifies the verb (analyze/extract/append), resource (video file), and outcome (adds to knowledge base). However, it doesn't explicitly differentiate from siblings like 'analyze_video_clip' or 'generate_hook_options' which might have overlapping functionality.

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 some usage context: 'Use this to build up your hook knowledge base from high-performing videos.' This implies it's for learning from successful videos, but it doesn't explicitly state when to use this versus alternatives like 'analyze_video_clip' or 'generate_hook_options', nor does it mention prerequisites or exclusions.

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