一键导入
create-prototype
Implements a single user story from the PRD: writes code and tests, follows project conventions. Invoked by: nvst create prototype.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
菜单
Implements a single user story from the PRD: writes code and tests, follows project conventions. Invoked by: nvst create prototype.
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Fixes one issue from the iteration issues list by reproducing, diagnosing, and resolving it. Invoked by: bun nvst fix issue.
Refines .agents/PROJECT_CONTEXT.md via editor mode or challenge mode. Challenge mode validates the document against the actual codebase and detects compliance issues. Triggered by: nvst refine project-context.
Leads a structured ideation interview to surface feature/project ideas and update ROADMAP.md with new candidates.
Creates or updates .agents/PROJECT_CONTEXT.md with project conventions, tech stack, code standards, testing strategy, and product architecture. Triggered by: nvst create project-context.
Drive interactive approval of the prototype by updating project context and roadmap artifacts after a completed iteration.
Load the refactor plan from it_{iteration}_audit.json and invoke the agent to apply code changes.
| name | create-prototype |
| description | Implements a single user story from the PRD: writes code and tests, follows project conventions. Invoked by: nvst create prototype. |
| user-invocable | true |
Implement the provided user story by writing production code and tests that satisfy all acceptance criteria, following the project's conventions and architecture.
Use Chain of Draft (CoD) for all internal reasoning before writing code or producing prompts.
lessons_learned context variable is present and non-empty, read it carefully before planning. It contains insights from previous agents working on this iteration. Skip this step silently if lessons_learned is absent or empty.| Source | Used for |
|---|---|
user_story (context variable) | The user story JSON with id, title, description, and acceptanceCriteria |
project_context (context variable) | Project conventions, tech stack, code standards, testing strategy, and architecture |
iteration (context variable) | Current iteration number for file naming and context |
lessons_learned (context variable) | Accumulated insights from previous agents in this iteration; empty string if none exist yet |
When user_story or iteration are not injected as context variables, resolve them using the following lookup order before asking the user:
state.json — read .agents/state.json (if it exists) to obtain current_iteration..agents/flow/it_{iteration}_PRD.json (preferred) — read the userStories array and present the available stories to the user, asking which one to implement..agents/flow/it_{iteration}_product-requirement-document.md (fallback) — read the file, identify the user stories listed, and ask the user which story to implement.state.json nor any PRD artifact can be found, ask the user to provide the 6-digit iteration number (e.g. 000037). Once the iteration is known, retry step 3.Before implementation, detect whether this is a UI task.
UI, interface, page, component, visual, button, form, layout, style, or frontend.frontend-design — set design direction and aesthetics.harden — handle UI edge cases and resilience.polish — run a final quality and refinement pass..agents/state.json or progress files — the calling command manages those.The output is the set of file changes (new files created, existing files modified) in the working tree. There is no document to produce — the code and tests are the deliverable.
Before finishing:
.agents/flow/{lessons_learned_file}After completing your user story, create or append a lessons-learned entry to .agents/flow/{lessons_learned_file} (the lessons_learned_file context variable provides the exact filename for this PRD index, e.g. it_000043_lessons-learned_001.md).
Each entry must include the following sections:
## {User Story ID} — {User Story Title}
**Summary:** Brief description of what was implemented.
**Key Decisions:** Important architectural or design choices made during implementation.
**Pitfalls Encountered:** Any mistakes, unexpected behaviours, or dead ends hit during implementation.
**Useful Context for Future Agents:** Any discoveries, patterns, or caveats that will help the next agent working on this codebase.
# Lessons Learned — Iteration {iteration} followed by the entry.lessons_learned_file context variable (e.g. it_000043_lessons-learned_001.md), consistent with other flow artifacts in .agents/flow/.