commit
免费Create a conventional commit for all uncommitted changes
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Execute or resume an implementation plan from `.agents/local/plans/`, keeping its companion backlog and validation evidence current. Use when the user asks to implement a saved plan or continue planned multi-phase work.
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实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Use the plan path supplied with the request. If no path is supplied, proceed only when one plan is the unambiguous subject of the conversation; otherwise ask which plan to execute.
.agents/rules/ that matches the files in scope; the plan may name additional mandatory rule files..agents/local/plans/backlogs/ for an existing backlog. If one exists, resume from the first [ ] or [~] item instead of starting over.For each task:
If something in the plan is wrong or missing, document the deviation in the backlog and continue; do not silently diverge.
Create the test files the plan specifies, following the existing test organization (unit tests for operations, integration tests for handlers). Cover the edge cases the plan lists.
./manage.py proto # if .proto files changed
./manage.py lint -s backend # if Python changed
./manage.py lint -s ui # if frontend changed
./manage.py test # backend tests
./manage.py test -s ui # frontend tests
Fix and re-run until green. Do not skip validation steps.
[x], in-progress [~] with a note, blocked [!] with the reason.Summarize: tasks completed, files created/modified, tests added with results, validation output, deviations from the plan. State plainly whether the work is ready for the commit skill.
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Create a conventional commit for all uncommitted changes
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Create a Product Requirements Document from the current conversation and save it under `.agents/local/plans/`. Use when the user asks for a PRD, product specification, or requirements document for an Uniffy feature.
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Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
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Audit the in-tree model catalog against each provider's live API (Anthropic, OpenAI, Google, OpenRouter, xAI) using the keys in .env. Surfaces new models the catalog is missing, catalog models a provider no longer returns, and price/context drift on the curated OpenRouter subset, so the catalog stays current. Works on both stacks (docker containers or host venv). Run periodically or when a provider ships new models / changes pricing.
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Create a comprehensive Uniffy feature plan in `.agents/local/plans/` through deep codebase analysis, applicable rules, verified patterns, risks, tests, and executable validation steps. Use when the user asks to plan a feature or prepare implementation work without writing product code.
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Check the current branch for an existing PR and either update or create one with an auto-generated description based on all commits since diverging from main.
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