create_tweet
Post a tweet to X. Enter the tweet text to publish it with AI-guided writing and refinement.
Instructions
Create a tweet
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Post a tweet to X. Enter the tweet text to publish it with AI-guided writing and refinement.
Create a tweet
| Name | Required | Description | Default |
|---|---|---|---|
| text | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral transparency. 'Create a tweet' implies mutation but offers no details about rate limits, authentication requirements, or any constraints (e.g., character limits), leaving significant behavioral traits undisclosed.
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 extremely short (3 words), which is concise but at the expense of essential information. It is under-specified, lacking structure or any front-loading of key details, making it insufficient for effective tool selection.
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 simplicity of the tool (one parameter, no output schema, no annotations), a complete description should at least clarify the nature of the 'text' parameter (e.g., tweet content, character limits). The current description is incomplete, leaving the agent without necessary context to use the tool correctly.
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% description coverage for the 'text' parameter, and the tool description does not add any meaning beyond the schema. The agent has no information about what 'text' should contain (e.g., tweet content, formatting, length constraints), rendering the parameter semantics entirely dependent on inference.
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 'Create a tweet' clearly states the verb and resource, making the tool's purpose immediately understandable. However, it is minimal and does not differentiate from any potential siblings, but since no siblings exist, it is adequate.
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 no guidance on when to use this tool or any alternatives. There are no sibling tools, but the lack of context (e.g., prerequisites, typical use cases) means the agent has no additional decision support.
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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