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Survey Generator

Turns arXiv surveys or awesome-lists into structured wiki markdown instead of throwaway HTML. You point it at a public anchor resource, it extracts a taxonomy and real paper citations, then sends everything to your choice of LLM (Anthropic, OpenAI, OpenRouter, Fireworks, custom) to write the prose. Output lands in your wiki's `derived/surveys/` with full bibliography rows appended to `sources.md`, so the research loop can build on it later. Good for onboarding a new domain or synthesizing what you've already collected. The workflow enforces real citations only and lets you compare providers by running the same bundle through different models. It's provider-agnostic by design, which matters when you want reproducible research artifacts that aren't locked to one vendor.

skills.sh installs
154
GitHub stars
2.9K
last updated
Jun 8, 2026

Install

$ npx -y skills add rohitg00/pro-workflow --skill survey-generator --agent claude-code

Installs into .claude/skills of the current project.

Files

Survey Generator

Provider-agnostic literature-survey artifact generator. Output flows into a pro-workflow wiki, not a standalone HTML file — survives sessions and indexes for FTS5 retrieval.

Diff vs dair-academy version

dairpro-workflow
Hardcoded Kimi K2.6 on FireworksProvider-agnostic (Anthropic/OpenAI/OpenRouter/Fireworks/custom)
Output = single-file HTML with inline SVGOutput = wiki markdown page + bibliography rows in sources.md
One-off artifact, no follow-upPersists in FTS5 index; reused by wiki-research-loop
Manual run onlyComposable with /wiki research for auto-bibliography expansion

When to use

  • "Survey on " / "lit review on "
  • Onboarding a new domain — generate the map-of-the-field
  • After a wiki has 10-30 sources, compile a synthesis page over them
  • Pre-step before /wiki research runs: gives the loop a high-quality seed bundle

Inputs

Sponsors

Details

Repository
github.com/rohitg00/pro-workflow
Categories
Frontend Development, Git & Pull Requests, Documentation, Code Review & Quality, AI & Agent Building, Data Science & ML, Automation & Workflows
First seen
Jun 11, 2026

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