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generate_code

Generate React components with shadcn/ui and Tailwind CSS from design specifications. Converts saved specs into production-ready code files organized by atomic design structure.

Instructions

Generate shadcn/ui + Tailwind component code from a saved spec and write output files to the project.

Prerequisites: The spec must exist in the registry (use get_specs to list names, create_spec to create one). Output is written into atomic design folders: atoms → components/ui/, molecules → components/molecules/, organisms → components/organisms/, templates → components/templates/.

Returns on success: { entryFile: string (absolute path to main generated file), files: string[] (all generated file paths), generatedAt: ISO timestamp }

Error behavior: Throws if specName is not found. If code generation fails (e.g. schema mismatch), an error message is returned with the failure reason.

Use this tool: after create_spec to turn a spec into working code. For pages, the page spec must reference template and component specs that already exist. Run npm install to add any missing shadcn components after generation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specNameYesName of the spec to generate code for (case-sensitive, must match a spec returned by get_specs).
Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behaviors: it writes files to specific folders (destructive operation), requires prerequisites (spec existence), returns structured data on success, and throws errors for missing specs or generation failures. It also mentions post-generation steps (npm install), adding useful context beyond basic functionality.

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

Conciseness4/5

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

The description is appropriately sized and front-loaded, starting with the core purpose. Most sentences earn their place by providing essential information like prerequisites, output structure, error behavior, and usage guidelines. However, some details (e.g., folder structures) could be slightly condensed without losing clarity.

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

Completeness5/5

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

Given the tool's complexity (code generation with file writes) and lack of annotations or output schema, the description is complete enough. It covers purpose, prerequisites, output format (including return structure), error behavior, usage context, and post-generation steps, providing all necessary information for an agent to use the tool effectively.

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 the single parameter (specName) with its type, description, and constraints. The description adds minimal value beyond the schema by implying specName usage but doesn't provide additional syntax or format details. Baseline 3 is appropriate when the schema does the heavy lifting.

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

Purpose5/5

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

The description clearly states the tool's purpose with specific verbs ('generate', 'write') and resources ('shadcn/ui + Tailwind component code', 'output files'), distinguishing it from siblings like create_spec (which creates specs) or get_specs (which lists specs). It explicitly mentions generating code from a saved spec and writing files to the project.

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

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit guidance on when to use this tool ('after create_spec to turn a spec into working code'), prerequisites ('The spec must exist in the registry'), and alternatives ('use get_specs to list names, create_spec to create one'). It also mentions specific conditions for pages and post-generation steps like running npm install.

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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