suggest_clips

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

With no annotations, the description fully explains behavior: stores suggestions, assigns clip numbers, pushes to UI. While it doesn't detail persistence or authorization, it sufficiently discloses the tool's actions and outcomes.

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 with step indicators and clear sections. It is slightly verbose but every sentence provides useful context, making it concise enough for effective agent use.

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 simple parameter structure and no output schema, the description covers the tool's role in a multi-step workflow. It explains inputs, processing, and follow-up actions, though it omits the return format.

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 100%, so baseline is 3. The description does not add additional meaning to the parameters beyond what the schema already provides. It mentions clip numbers but not in relation to 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?

The description clearly states the tool's purpose: 'Submit your clip suggestions after analyzing the transcript.' It specifies that it stores suggestions, assigns clip numbers, and pushes to the Web UI, effectively distinguishing it from siblings like create_clip and batch_create_clips.

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 explicit before/after steps: 'Before calling this: read the transcript... identify the best viral moments.' and 'After this: the user reviews in the UI. Then export with batch_create_clips or create_clip.' This gives clear workflow context.

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