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generate_code

Generate programming code in various languages based on descriptive input and additional requirements.

Instructions

Generate code based on a description

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
descriptionYesDescription of the code to generate
languageNoProgramming language (e.g., JavaScript, Python, TypeScript)
additionalContextNoAdditional context or requirements for the code
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action ('generate code') without mentioning permissions, rate limits, response format, or any constraints. This is inadequate for a tool with potential complexity in code generation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with a single sentence ('Generate code based on a description'), which is front-loaded and wastes no words. However, this conciseness comes at the cost of completeness, as noted in other dimensions.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity of code generation, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, usage context, and output expectations, making it insufficient for an AI agent to understand the tool fully.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents all three parameters. The description adds no meaning beyond what the schema provides, as it doesn't explain parameter interactions or usage examples. Baseline 3 is appropriate since the schema does the heavy lifting.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states what the tool does ('Generate code based on a description'), which is clear but vague. It specifies the verb 'generate' and resource 'code', but doesn't distinguish it from sibling tools like 'generate_code_to_file' or 'generate_documentation', leaving ambiguity about scope and output format.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

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 versus alternatives. There are sibling tools like 'generate_code_to_file' and 'generate_documentation', but no explicit or implied context for choosing between them, such as output destination or purpose.

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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