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generate_adr_bootstrap

Generate bootstrap and validation scripts to enforce ADR compliance. Merge base repository code before generation to call validated patterns, ensuring deployments follow architecture decisions.

Instructions

Generate bootstrap.sh and validate_bootstrap.sh scripts to ensure deployed code follows ADR requirements. CRITICAL: Before generating scripts, use WebFetch to query the base code repository (e.g., https://github.com/validatedpatterns/common for OpenShift) and authoritative pattern documentation (e.g., https://play.validatedpatterns.io/). Merge the base repository code into your project and have bootstrap.sh call the pattern's scripts rather than generating everything from scratch. This ensures compliance with validated deployment patterns.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectPathNoPath to the project directory.
adrDirectoryNoDirectory where ADRs are storeddocs/adrs
outputPathNoDirectory where to generate scripts.
scriptTypeNoWhich scripts to generateboth
includeTestsNoInclude test execution in bootstrap
includeDeploymentNoInclude deployment steps in bootstrap
customValidationsNoCustom validation commands to include
conversationContextNoRich context from the calling LLM about user goals and discussion history
Behavior2/5

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

No annotations are provided, so the description must fully disclose behavior. It states script generation but also implies code merging which may not be a tool action. Lacks details on side effects, permissions, or output.

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

Conciseness3/5

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

Single paragraph but includes lengthy critical workflow instructions. The critical part adds noise relative to the tool's core function. Could be more concise.

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 8 parameters, a nested object, and no output schema, the description should explain what the tool generates and how results are structured. It focuses on pre-work, not on tool's own behavior or return values.

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 coverage is 100% with descriptions. The description adds no extra parameter meaning beyond repeating what schema provides, so baseline 3 is appropriate.

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 tool generates bootstrap and validate scripts. However, the immediately following critical instruction about using WebFetch first muddles the direct purpose, making it less crisp.

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

Usage Guidelines4/5

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

Explicitly instructs to use WebFetch before generating scripts, providing clear context. Does not mention when not to use or alternatives, but the workflow guidance is valuable.

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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