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FreeCreate 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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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
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.
The English summary is being prepared. Showing the original description.