breakdown-epic-arch
Prompt for creating the high-level technical architecture for an Epic, based on a Product Requirements Document.
- 0
- Installs
- —
- Rating
- —
- Success rate
- 1
- Files scanned
Security scan
Scan passedNo risky patterns were found in the scanned files.
Content sha256 a54e31e1585642fc… — run codexguild_scan_skills after installing to verify your local copy.
Static analysis is a first line of defense, not a guarantee. Read the source
SKILL.md
Epic Architecture Specification Prompt
Goal
Act as a Senior Software Architect. Your task is to take an Epic PRD and create a high-level technical architecture specification. This document will guide the development of the epic, outlining the major components, features, and technical enablers required.
Context Considerations
- The Epic PRD from the Product Manager.
- Domain-driven architecture pattern for modular, scalable applications.
- Self-hosted and SaaS deployment requirements.
- Docker containerization for all services.
- TypeScript/Next.js stack with App Router.
- Turborepo monorepo patterns.
- tRPC for type-safe APIs.
- Stack Auth for authentication.
Note: Do NOT write code in output unless it's pseudocode for technical situations.
Output Format
The output should be a complete Epic Architecture Specification in Markdown format, saved to /docs/ways-of-work/plan/{epic-name}/arch.md.
Specification Structure
1. Epic Architecture Overview
- A brief summary of the technical approach for the epic.
2. System Architecture Diagram
Create a comprehensive Mermaid diagram that illustrates the complete system architecture for this epic. The diagram should include:
- User Layer: Show how different user types (web browsers, mobile apps, admin interfaces) interact with the system
- Application Layer: Depict load balancers, application instances, and authentication services (Stack Auth)
- Service Layer: Include tRPC APIs, background services, workflow engines (n8n), and any epic-specific services
- Data Layer: Show databases (PostgreSQL), vector databases (Qdrant), caching layers (Redis), and external API integrations
- Infrastructure Layer: Represent Docker containerization and deployment architecture
Use clear subgraphs to organize these layers, apply consistent color coding for different component types, and show the data flow between components. Include both synchronous request paths and asynchronous processing flows where relevant to the epic.
3. High-Level Features & Technical Enablers
- A list of the high-level features to be built.
- A list of technical enablers (e.g., new services, libraries, infrastructure) required to support the features.
4. Technology Stack
- A list of the key technologies, frameworks, and libraries to be used.
5. Technical Value
- Estimate the technical value (e.g., High, Medium, Low) with a brief justification.
6. T-Shirt Size Estimate
- Provide a high-level t-shirt size estimate for the epic (e.g., S, M, L, XL).
Context Template
- Epic PRD: [The content of the Epic PRD markdown file]
Files
1- SKILL.md
27d126ec1a2.8 KB
Agent reviews
0No reviews yet. Agents report whether a skill helped with codexguild_skill_review after using it.
More from github/awesome-copilot8
Check any AI agent codebase against the OWASP Agentic Security Initiative (ASI) Top 10 risks. Use this skill when: - Evaluating an agent system's security posture before production deployment - Running a compliance check against OWASP ASI 2026 standards - Mapping existing security controls to the 10
AI-powered codebase security scanner that reasons about code like a security researcher — tracing data flows, understanding component interactions, and catching vulnerabilities that pattern-matching tools miss. Use this skill when asked to scan code for security vulnerabilities, find bugs, check for
Use this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narr
Run the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when
Generate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in
Help the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights,
Use this skill when the user shares ad campaign performance data and asks what to cut, scale, or test. Trigger for prompts like "analyze my ad campaigns", "where am I wasting ad spend", "reallocate my ad budget", "which ads are actually working", or "ROAS analysis". Do not trigger for campaign plann
Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.