gsd-execute-phase
SolidExecute all plans in a phase with wave-based parallelization
AI & Automation 6 stars
0 forks Updated yesterday MIT
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Skill Content
<cursor_skill_adapter>
## A. Skill Invocation
- This skill is invoked when the user mentions `gsd-execute-phase` or describes a task matching this skill.
- Treat all user text after the skill mention as `{{GSD_ARGS}}`.
- If no arguments are present, treat `{{GSD_ARGS}}` as empty.
## B. User Prompting
When the workflow needs user input, prompt the user conversationally:
- Present options as a numbered list in your response text
- Ask the user to reply with their choice
- For multi-select, ask for comma-separated numbers
## C. Tool Usage
Use these Cursor tools when executing GSD workflows:
- `Shell` for running commands (terminal operations)
- `StrReplace` for editing existing files
- `Read`, `Write`, `Glob`, `Grep`, `Task`, `WebSearch`, `WebFetch`, `TodoWrite` as needed
## D. Subagent Spawning
When the workflow needs to spawn a subagent:
- Use `Task(subagent_type="generalPurpose", ...)`
- The `model` parameter maps to Cursor's model options (e.g., "fast")
</cursor_skill_adapter>
<objective>
Execute all plans in a phase using wave-based parallel execution.
Orchestrator stays lean: discover plans, analyze dependencies, group into waves, spawn subagents, collect results. Each subagent loads the full execute-plan context and handles its own plan.
Optional wave filter:
- `--wave N` executes only Wave `N` for pacing, quota management, or staged rollout
- phase verification/completion still only happens when no incomplete plans remain after the selected wave finishes
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Details
- Author
- friday-ai-codes
- Repository
- friday-ai-codes/friday-ai
- Created
- 1 months ago
- Last Updated
- yesterday
- Language
- Python
- License
- MIT
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