skills/09-meleantonio-awesome-econ-ai-stuff/_skills/engineering/sdd/SKILL.md
Implements the Spec-Driven Development lifecycle (Intent, Requirements, Design, Tasks, Build) for structured feature development. Use when the user wants to scaffold a new feature spec, generate EARS requirements, create a technical design, break work into tasks, or check spec status. Trigger on keywords: sdd, spec-driven, ears requirements, feature spec.
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research sddInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Execute in the project root (where spec/ and steering/ live).
initScaffold the SDD folder structure and template files.
spec/ already exists, skip or ask before overwriting.spec/ and steering/.spec/intent.md (blank or minimal placeholder).templates/ directory (in the same folder as SKILL.md, or from your install path under ~/.cursor/skills/sdd/ after copying the skill there) into the project:
templates/spec/requirements.md → spec/requirements.mdtemplates/spec/design.md → spec/design.mdtemplates/spec/tasks.md → spec/tasks.mdtemplates/steering/coding-standards.md → steering/coding-standards.mdreqsGenerate EARS requirements from intent.
spec/intent.md and steering/*.md.spec/requirements.md.designGenerate technical design from requirements.
spec/requirements.md and steering/*.md.spec/design.md.tasksGenerate implementation tasks from design.
spec/design.md and spec/requirements.md.REQ-001). Follow Task Rules below.spec/tasks.md.statusReport current state of the spec.
spec/ (and optionally steering/).spec/tasks.md exists, count unchecked [ ] vs checked [x] and summarize.<system> shall <response>WHEN <trigger> [precondition] the <system> shall <response>IF <unwanted condition> THEN the <system> shall <response>WHILE <system state>, the <system> shall <response>WHERE <feature is included>, the <system> shall <response>Use IDs like [REQ-001]; add a Properties (Invariants) section for universal correctness statements.
REQ-001).tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.