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generate_dockerfile

Create Dockerfile templates for programming languages like Node.js, Python, Java, Go, and Rust with framework-specific optimizations to containerize applications.

Instructions

Generate a Dockerfile template for a specific language/framework

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageYesProgramming language for the Dockerfile
frameworkNoFramework-specific optimizations (e.g., alpine, express, fastapi)
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It states it 'generates' a template, implying a read-only creation operation, but doesn't specify if it writes to a file, returns content, requires permissions, or has side effects. For a 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.

Conciseness5/5

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

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part ('generate', 'Dockerfile template', 'specific language/framework') contributes directly to understanding, making it appropriately sized and zero-waste.

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 no annotations and no output schema, the description is incomplete for a tool that likely returns generated content. It doesn't explain what the output looks like (e.g., string, file path), error conditions, or dependencies. For a 2-parameter tool with zero structured coverage, the description should do more to compensate, especially regarding behavioral aspects.

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%, with clear descriptions for both parameters. The description adds minimal value beyond the schema, mentioning 'language/framework' which aligns with parameter names but doesn't provide additional context like default behaviors or interaction between parameters. 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.

Purpose4/5

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

The description clearly states the action ('generate') and the resource ('Dockerfile template'), specifying it's for a 'specific language/framework'. It distinguishes from sibling tools like 'docker_build' or 'generate_docker_compose' by focusing on template creation rather than building or compose file generation. However, it doesn't explicitly differentiate from all siblings (e.g., 'generate_sample_config'), so it's not a perfect 5.

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. It doesn't mention when to choose this over 'docker_build' for actual building, 'generate_docker_compose' for orchestration, or other configuration tools. There's no context about prerequisites or typical use cases, leaving the agent to infer usage from the purpose alone.

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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