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worktree

Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, and generates Prisma client. TRIGGER when user asks to set up a worktree, work on a branch in isolation, or needs a separate environment for a branch or PR.

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
The actual content of the system_prompt field in the .skill file.
name worktree description Set up a new git worktree for parallel development. Creates the worktree, copies .env files, installs dependencies, and generates Prisma client. TRIGGER when user asks to set up a worktree, work on a branch in isolation, or needs a separate environment for a branch or PR. user-invocable true args [name] — optional worktree name (e.g., 'AutoGPT7'). If omitted, uses next available AutoGPT<N>. metadata {"author":"autogpt-team","version":"3.0.0"} Worktree Setup Create the worktree Derive paths from the git toplevel. If a name is provided as argument, use it. Otherwise, check git worktree list and pick the next AutoGPT<N> . ROOT=$(git rev-parse --show-toplevel) PARENT=$( dirname " $ROOT " ) # From an existing branch git worktree add " $PARENT /<NAME>" <branch-name> # From a new branch off dev git worktree add -b <new-branch> " $PARENT /<NAME>" dev Copy environment files Copy .env from the root worktree. Falls back to .env.default if .env doesn't exist. ROOT=$(git rev-parse --show-toplevel) TARGET= " $(dirname " $ROOT " ) /<NAME>" for envpath in autogpt_platform/backend autogpt_platform/frontend autogpt_platform; do if [ -f " $ROOT / $envpath /.env" ]; then cp " $ROOT / $envpath /.env" " $TARGET / $envpath /.env" elif [ -f " $ROOT / $envpath /.env.default" ]; then cp " $ROOT / $envpath /.env.default" " $TARGET / $envpath /.env" fi done Install dependencies TARGET= " $(dirname " $(git rev-parse --show-toplevel) " ) /<NAME>" cd " $TARGET /autogpt_platform/autogpt_libs" && poetry install cd " $TARGET /autogpt_platform/backend" && poetry install && poetry run prisma generate cd " $TARGET /autogpt_platform/frontend" && pnpm install Replace <NAME> with the actual worktree name (e.g., AutoGPT7 ). Running the app (optional) Backend uses ports: 8001, 8002, 8003, 8005, 8006, 8007, 8008. Free them first if needed: TARGET= " $(dirname " $(git rev-parse --show-toplevel) " ) /<NAME>" for port in 8001 8002 8003 8005 8006 8007 8008; do lsof -ti : $port | xargs kill -9 2>/dev/null || true done cd " $TARGET /autogpt_platform/backend" && poetry run app CoPilot testing SDK mode spawns a Claude subprocess — won't work inside Claude Code. Set CHAT_USE_CLAUDE_AGENT_SDK=false in backend/.env to use baseline mode. Cleanup # Replace <NAME> with the actual worktree name (e.g., AutoGPT7) git worktree remove " $(dirname " $(git rev-parse --show-toplevel) " ) /<NAME>" Alternative: Branchlet (optional) If branchlet is installed: branchlet create -n <name> -s <source-branch> -b <new-branch>
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The downloaded .skill package contains the following fields.
Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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