createTwitchClip
Create a Twitch clip from the current live stream to capture and share memorable moments with viewers.
Instructions
Create a Twitch clip of the current stream
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Create a Twitch clip from the current live stream to capture and share memorable moments with viewers.
Create a Twitch clip of the current stream
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the tool creates a clip but doesn't reveal critical traits: whether this requires broadcaster permissions, how long the clip is, if it's saved automatically, rate limits, or what happens on failure. For a mutation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior and safety profile.
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 a single, front-loaded sentence that directly states the tool's function without any fluff or redundant information. Every word earns its place by conveying the essential action and target. It's appropriately sized for a simple tool with no parameters, making it highly efficient and easy to parse.
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 as a mutation operation with no annotations and no output schema, the description is incomplete. It lacks details on permissions, clip duration, success/failure responses, and how it interacts with the streaming context. For a tool that modifies state in a live environment, more context is needed to ensure safe and effective use by an agent.
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 0 parameters with 100% coverage, meaning no parameters are documented in the schema. The description doesn't add parameter details, which is appropriate since none exist. It implies the tool operates on the current stream without needing inputs, which aligns with the schema. Baseline 4 is given for zero-parameter tools where the description doesn't need to compensate for schema 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 action ('create') and target resource ('Twitch clip of the current stream'), making the purpose immediately understandable. It doesn't explicitly differentiate from sibling tools like 'createTwitchPoll' or 'createTwitchPrediction', but the specificity of 'clip' versus 'poll/prediction' provides inherent distinction. The description avoids tautology by not just restating the tool name.
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 minimal guidance on when to use this tool, only implying it's for creating clips during a live stream. It doesn't mention prerequisites (e.g., requires an active stream), exclusions (e.g., cannot create clips from VODs), or alternatives among siblings (e.g., when to use this versus other creation tools like polls). Without explicit usage context, the agent must infer timing and constraints.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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