Convert vague user goals into testable acceptance criteria with codebase analysis.
npx skills add https://github.com/kurioscreative/skills --skill shape-kurioscreative
Please help me install this Agent Skill. Skill: shape Source: https://github.com/kurioscreative/skills/tree/main/skills/shape Command: npx skills add https://github.com/kurioscreative/skills --skill shape-kurioscreative
This Skill addresses the issue of translating a high-level, unclear goal into a concrete, testable contract, enabling effective communication and execution between a human and AI agent.
Shape the goal "Refactor authentication process for better scalability" into a testable task contract.
High-intent search queries and answers about installing and using this skill.
To convert vague software development goals into testable acceptance criteria, you can use an agentic workflow to analyze your codebase and translate high-level intent into specific, machine-verifiable task contracts.
A task contract in an agentic workflow is a concrete, testable Markdown block that defines explicit acceptance criteria, ensuring human-to-machine handoffs have the clarity required for effective execution.
To clarify requirements for an AI agent before refactoring a codebase, you must transform ambiguous goals into explicit, machine-verifiable criteria grounded by analyzing the existing code structure.
You do not need an existing codebase to generate machine-testable contracts, but utilizing codebase analysis capabilities helps validate and refine the acceptance criteria to ground the goal in reality.
You can automatically validate acceptance criteria against your current codebase by leveraging codebase analysis features that refine the generated task contracts based on existing project context.
The best way to define machine-verifiable criteria for software development tasks is converting expressed goals into a Markdown task contract, enabling clear communication and execution between human and AI agent.
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