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generate_adrs_from_prd

Generate structured Architectural Decision Records from a Product Requirements Document using automatic prompt optimization and knowledge generation.

Instructions

Generate Architectural Decision Records from a Product Requirements Document with advanced prompting techniques (APE + Knowledge Generation)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
prdPathYesPath to the PRD.md file
prdTypeNoType of PRD for optimized knowledge generationgeneral
enhancedModeNoEnable advanced prompting features (APE + Knowledge Generation)
outputDirectoryNoDirectory to output generated ADRs (optional, uses configured ADR_DIRECTORY if not provided)
promptOptimizationNoEnable Automatic Prompt Engineering for optimized ADR generation
conversationContextNoRich context from the calling LLM about user goals and discussion history
knowledgeEnhancementNoEnable Knowledge Generation for domain-specific insights
Behavior2/5

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

With no annotations provided, the description must carry the full burden of behavioral disclosure. It mentions advanced prompting and parameters like enhancedMode, but does not disclose side effects (e.g., file creation), required permissions, or rate limits. Critical behavioral traits are missing.

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 a single sentence of 16 words, which is very concise and front-loaded. However, it lacks structural elements like bullet points or sections that could improve readability. Overall, it is efficient but could be optimized.

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 tool has 7 parameters including a nested object (conversationContext with 10 sub-fields) and no output schema, the description is incomplete. It does not explain what the output is (e.g., generated ADR files), how the context is used, or provide a link to expected results. Critical context is missing.

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 baseline is 3. The description does not add significant meaning beyond the schema; it references 'advanced prompting techniques' but does not elaborate on how each parameter affects behavior. The explanation of conversationContext is minimal and redundant with the schema.

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: generating Architectural Decision Records from a Product Requirements Document. It specifies the resource (PRD file) and distinguishes itself from sibling tools like generate_adr_bootstrap or generate_adr_from_decision by mentioning advanced prompting techniques (APE + Knowledge Generation).

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

Usage Guidelines3/5

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

The description implies usage when a PRD exists and advanced ADR generation is desired, but it does not provide explicit guidance on when to use this tool versus alternatives like generate_adr_bootstrap or generate_adr_todo. No exclusions or comparison to siblings are given.

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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