Agent Rag Retrieval Tasks.tasks.prompt
---
id: 002
title: agent-rag-retrieval-tasks
stage: tasks
date: 2025-12-26
surface: agent
model: claude-sonnet-4-5-20250929
feature: agent-rag-retrieval
branch: 001-agent-rag-retrieval
user: Claude
command: sp.tasks
labels: [tasks, agent, rag, retrieval, openai]
links:
spec: specs/001-agent-rag-retrieval/spec.md
tasks: specs/001-agent-rag-retrieval/tasks.md
ticket: null
adr: null
pr: null
files:
- specs/001-agent-rag-retrieval/tasks.md
tests:
- specs/001-agent-rag-retrieval/tasks.md validates task breakdown for agent implementation
---
## Prompt
generate tasks be concise
## Response snapshot
Generated comprehensive tasks.md file for the OpenAI Agent with Retrieval-Augmented Capabilities feature. The tasks are organized in phases following the user story priorities from the specification:
- Phase 1: Setup (project initialization)
- Phase 2: Foundational (blocking prerequisites)
- Phase 3: User Story 1 - Agent Creation and Basic Query (P1 - MVP)
- Phase 4: User Story 2 - Tool-Based Retrieval Integration (P2)
- Phase 5: User Story 3 - Follow-up Query Handling (P3)
- Phase N-1: Documentation & Examples
- Phase N: Polish & Cross-Cutting Concerns
Each task follows the required format with ID, story labels, and specific file paths. The tasks are organized to enable independent implementation and testing of each user story, with clear dependencies and parallel execution opportunities identified.
## Outcome
- ✅ Impact: Created complete task breakdown for agent implementation
- 🧪 Tests: Tasks include validation checkpoints for each user story
- 📁 Files: Created tasks.md with 28 specific implementation tasks
- 🔁 Next prompts: Ready for implementation with /sp.implement
- 🧠 Reflection: Tasks follow proper format and enable incremental delivery
## Evaluation notes (flywheel)
- Failure modes observed: None
- Graders run and results (PASS/FAIL): N/A
- Prompt variant (if applicable): N/A
- Next experiment (smallest change to try): Begin implementation with Phase 1 taskswhen to use it
Community prompt sourced from the open-source GitHub repo Waqar-5/AI_PHYSICAL_BOOK (no explicit license). A "Agent Rag Retrieval Tasks.tasks.prompt" style prompt — adapt the placeholders and specifics to your task. Imported as-is and not independently retested here, so check the output before relying on it.
tags
productivitycommunitydeveloper
source
Waqar-5/AI_PHYSICAL_BOOK · no explicit license
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