Survey Generator
Compile a structured literature survey on any AI/ML topic.
Install
npx skills add rohitg00/pro-workflow --skill survey-generator -g -a claude-code -y- Repository
- rohitg00/pro-workflow2.9k
- Category
- Data and ML
- Updated
- 1mo ago
- License
- See repository
- Context cost
- Lightabout 1,416 tokens
- Runs scripts
- Yes, review before use
What it does
Compile a structured literature survey on any AI/ML topic. Agent curates a research bundle (taxonomy + sections + bibliography of real papers) from a public anchor resource, then a chosen LLM generates the survey artifact. Output target is a wiki page (markdown), not a one-off HTML, survey lands in `<wiki>/derived/surveys/<slug>.md` with full bibliography rows in `sources.md`. Provider-agnostic (Anthropic/OpenAI/OpenRouter/Fireworks/custom OpenAI-compat). Use when the user asks for a "survey", "literature review", "lit review", or "deep dive" on a technical topic.
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
| dair | pro-workflow |
|---|---|
| Hardcoded Kimi K2.6 on Fireworks | Provider-agnostic (Anthropic/OpenAI/OpenRouter/Fireworks/custom) |
| Output = single-file HTML with inline SVG | Output = wiki markdown page + bibliography rows in sources.md |
| One-off artifact, no follow-up | Persists in FTS5 index; reused by wiki-research-loop |
| Manual run only | Composable with /wiki research for auto-bibliography expansion |
When to use
- "Survey on <topic>" / "lit review on <topic>"
- 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 researchruns: gives the loop a high-quality seed bundle
Inputs
| Input | Required | Description |
|---|---|---|
topic | yes | "Reasoning Models", "Agentic Engineering" |
source_url | yes | Public anchor: arXiv survey, GitHub awesome-list, canonical blog post |
--wiki <slug> | yes | Target wiki for the artifact |
--bibliography-size N | no | Default 20. 40-50 comprehensive, 80-100 exhaustive |
--section-count N | no | Default 6-10 numbered sections |
--provider name | no | Override provider (default: first explicitly configured provider) |
--model id | no | Override model |
Workflow (the agent runs these in order)
Step 1, Read the anchor
WebFetch source_url. Extract subtopics + cited papers. For GitHub awesome-lists, walk README + linked papers files. For arXiv survey PDFs, use abstract + ToC.
Step 2, Build research_bundle.json
Use templates/research_bundle.template.json as scaffold. Required keys:
