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Design and write comprehensive software documentation (README, architecture, API, runbooks, ADRs, user guides). Use when creating new docs, restructuring existing docs, or tuning docs for a specific audience (developer, operator, end user, stakeholder).
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
| name | documentation-expert |
| description | Design and write comprehensive software documentation (README, architecture, API, runbooks, ADRs, user guides). Use when creating new docs, restructuring existing docs, or tuning docs for a specific audience (developer, operator, end user, stakeholder). |
Create documentation that is accurate, discoverable, and tuned to its audience.
| Audience | Artefact |
|---|---|
| Contributors (new) | README, CONTRIBUTING, local setup |
| Contributors (deep) | Architecture overview, ADRs, module docs |
| API consumers | OpenAPI reference, SDK guides (delegate to api-documenter) |
| Operators | Runbooks, on-call guides, SLOs, incident response |
| End users | Getting started, feature guides, troubleshooting, FAQ |
| Stakeholders | Release notes, roadmaps, whitepapers |
# ADR NNNN: <decision>
- Status: Proposed | Accepted | Superseded by ADR-XXXX
- Date: YYYY-MM-DD
- Context: <what problem, what forces>
- Decision: <what we chose>
- Consequences: <positive, negative, trade-offs>
- Alternatives considered: <briefly, with reasons not chosen>
Strategy-layer agent planner. Analyses a complex request and recommends which subagents and skills to involve, in what order, with what hand-off. Use only for genuinely multi-domain tasks where the default delegation isn't obvious.
Design and build LLM-powered applications — RAG systems, agentic workflows, vector search, prompt pipelines, tool-using agents. Use for shipping production AI features, chatbots, or any AI-driven feature that goes beyond a one-shot prompt.
Generate developer-first API documentation: OpenAPI 3.1 specs, multi-language code examples, Postman collections, auth guides, and error references. Use when documenting a new API, adding endpoints, or when the user asks for OpenAPI/Postman/docs output.
Design scalable, secure, cost-efficient cloud infrastructure on AWS, Azure, or GCP. Terraform-first, FinOps-aware, multi-cloud and serverless patterns. Use for infrastructure planning, cost-reduction analysis, or cloud migration strategy.
Design context-management systems for AI-powered products — RAG, vector stores, knowledge graphs, episodic/semantic memory, multi-agent context handoff. Use when architecting AI features that need long-running or cross-session memory. Not for conversational context inside Cursor itself (handled by built-in compaction).
Design and build data-intensive systems — ETL/ELT pipelines, warehouses, streaming architectures. Expertise in Spark, Airflow, Kafka, dimensional modelling, governance, and cost optimisation. Use for new data solutions, optimising pipelines, or troubleshooting data infrastructure.