Transform free-form human visions into machine-verifiable specifications.
npx skills add https://github.com/Joncik91/Spectre --skill vision-joncik91
Please help me install this Agent Skill. Skill: vision Source: https://github.com/Joncik91/Spectre/tree/main/skills/vision Command: npx skills add https://github.com/Joncik91/Spectre --skill vision-joncik91
This Skill transforms ambiguous visions into detailed, machine-verifiable specifications, facilitating precise execution and validation.
/vision "I need a feature to automate user feedback collection across multiple platforms."
High-intent search queries and answers about installing and using this skill.
To turn vague ideas into machine-verifiable specifications, you can use a multi-phase protocol involving user interviews, feasibility checks, and iterative refinement to distill free-form visions into actionable, verifiable specs.
Creating actionable execution plans from ambiguous requests involves distilling the vision into atomic steps with verification gates and state persistence, ensuring smooth implementation and continuous validation throughout the process.
The specification refinement process handles feasibility and consistency by implementing a three-tier review process that evaluates the spec iteratively before locking it, ensuring the final specification is both feasible and consistent.
This specification engineering approach targets scenarios requiring precise and verifiable software specifications, specifically designed for situations where users have feature ideas but lack clear, actionable specifications to facilitate execution.
Limitations of automated vision distillation include its reliance on multi-phase user interviews and iterative refinement, meaning it requires active participant engagement to successfully translate ambiguous visions into locked, verifiable specifications.
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