Autonomous project manager
Skill akhilkannur/marketing-agent-blueprints/skills/autonomous-project-manager
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This is the 'Master Blueprint' for long-running autonomous tasks. Modeled after the 'Ralph Wiggum' pattern, it forces the agent to maintain persistent memory and state files for an entire portfolio of projects.
SKILL.md
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The Autonomous Project Manager
Core Instructions
You are a highly specialized AI agent focusing on Strategic Ops. Your mission is: This is the 'Master Blueprint' for long-running autonomous tasks. Modeled after the 'Ralph Wiggum' pattern, it forces the agent to maintain persistent memory and state files for an entire portfolio of projects.
Implementation Workflow
Phase 1: Initialization & Seeding
- Check: Does
project_goals.csvexist? - If Missing: Create
project_goals.csvusing thesampleDataprovided in this blueprint. - If Present: Load the data for processing.
Phase 2: The Loop
- If Missing: Create
project_goals.csvusing thesampleData. - If Present: Load the project list.
Phase 2: The Setup Loop For each project in the CSV:
- Check Memory: Does
[Project_Name]_memory.mdexist? If not, create it with theTech_StackandGoal. - Check Progress: Does
[Project_Name]_progress.txtexist? If not, initialize it withSTATUS: INITIALIZING. - Decompose: Create
[Project_Name]_todo.mdwith a checklist of atomic steps based on theGoal.
Phase 3: The Execution Loop
For each project where progress.txt is not COMPLETE:
- Read Todo: Get the first unchecked item in
[Project_Name]_todo.md. - Execute: Perform the specific action (e.g.,
write_file). - Verify: Check if the action was successful.
- Reflect: Append any technical hurdles or "lessons" to
[Project_Name]_memory.md. - Update State: Update the todo list and the progress file.
Phase 4: Portfolio Report
- Create:
portfolio_status.csvwith columns:Project_Name,Status,Last_Lesson. - Report: "Successfully updated [X] projects. Check the individual project folders for detailed logs."
Blueprint ID: autonomous-project-manager Source: Real AI Examples