Turn an approved task-analysis result into a shared technical design and coding-ready implementation handoff; use when Claude has an existing task folder under `tmp/tasks/`, plus a selected solution and related codebase research, and needs to produce `implementation-plan.md` and `coding-task.md` before writing code
Install via CLI
openskills install blockscout/blockscout-rs---
name: implementation-plan
description: Turn an approved task-analysis result into a shared technical design and coding-ready implementation handoff; use when Claude has an existing task folder under `tmp/tasks/`, plus a selected solution and related codebase research, and needs to produce `implementation-plan.md` and `coding-task.md` before writing code
disable-model-invocation: true
---
# Implementation Plan Skill
Follow the workflow defined in @../../../.memory-bank/workflows/implementation-plan.md
## Required Guardrails
- Read the existing task folder artifacts first, especially `task.md` and the selected solution.
- Re-check the current code, tests, configs, and schema paths instead of trusting earlier analysis blindly.
- Treat this as a handoff-preparation step, not a fresh solution-comparison step.
- If the chosen direction is ambiguous or stale enough to change the recommendation, stop and route the task back to analysis.
- Write the outputs into the existing `tmp/tasks/<task-name>/` folder as `implementation-plan.md` and `coding-task.md`.
- Keep the implementation plan focused on shared technical design; keep the coding task focused on actionable execution details.
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Python backend development expertise for FastAPI, security patterns, database operations, Upstash integrations, and code quality. Use when: (1) Building REST APIs with FastAPI, (2) Implementing JWT/OAuth2 authentication, (3) Setting up SQLAlchemy/async databases, (4) Integrating Redis/Upstash caching, (5) Refactoring AI-generated Python code (deslopification), (6) Designing API patterns, or (7) Optimizing backend performance.