survey-generator

Q: How do I install survey-generator?

Run npx skills add https://github.com/rohitg00/pro-workflow --skill survey-generator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/survey-generator/ (personal) or .claude/skills/survey-generator/ (project).

by rohitg00AI & Agents

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 /derived/surveys/ .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.

Installs: 135
Last 24h: —
Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/rohitg00/pro-workflow --skill survey-generator

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads survey-generator automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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 research runs: 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:

{
  "topic": "...",
  "anchor_source": "...",
  "abstract_hints": ["..."],
  "taxonomy": [{"branch": "...", "children": [{"name": "...", "description": "..."}]}],
  "sections": [{"title": "...", "guidance": "...", "papers": ["key1","key2"]}],
  "bibliography": [{"key": "author-year-shortname", "authors": "...", "year": 2024, "title": "...", "venue": "...", "summary": "..."}]
}

Hard rules:

Every paper in bibliography must be real. No invented entries.
Every key referenced in sections[].papers must exist in bibliography.
4-8 taxonomy branches, 2-4 children each.
6-10 numbered sections covering: introduction → foundations → methods → evaluation → open problems.

Step 3 — Run the generator

In a plugin session, call the providers MCP server's run_provider_task tool with task: "survey" and args: ["--bundle", "/absolute/path/research_bundle.json", "--wiki", "<slug>", "--provider", "openai"]. Keys come from the plugin configuration dialog. Never request keys in chat or retrieve existing machine credentials.

The direct commands below are for standalone CLI use with explicit PRO_WORKFLOW_*_API_KEY variables. See provider configuration.

node $SKILL_ROOT/scripts/build-survey.js \
  --bundle <path-to-research_bundle.json> \
  --wiki <slug> \
  [--provider anthropic|openai|openrouter|fireworks|custom] \
  [--model <id>]

Generator:

Reads bundle.
Sends to LLM with strict markdown spec (numbered sections, inline [^paper-key] citations, no HTML).
Writes output to <wiki>/derived/surveys/<topic-slug>.md.
Appends bibliography rows to <wiki>/sources.md (deduped by key).
Calls wiki-cli.js page to upsert into FTS5 index.

Step 4 — Iterate

If prose is thin: tighten sections[].guidance and rerun. Output filename versions automatically (<slug>-v2.md, <slug>-v3.md).

To compare providers:

node build-survey.js --bundle bundle.json --wiki agent-memory --provider openai --model gpt-4o
node build-survey.js --bundle bundle.json --wiki agent-memory --provider anthropic --model claude-opus-5-5

Each writes a separate versioned file; diff them.

Output structure

<wiki-root>/
├── sources.md                                 # bibliography rows appended (deduped)
└── derived/surveys/
    └── <topic-slug>-v1.md                     # the survey
        # title (h1)
        # ## 1. Introduction
        # ## 2. Foundations
        # ...
        # ## References
        # [^src-bib-<slug>] author year. title. venue.

Hard rules

Never invent bibliography entries — every paper must be a real work with venue.
Every section's papers array references keys in bibliography.
Output is markdown ONLY. No HTML, no inline SVG, no JS.
Bibliography rows in sources.md use the slug-style id src-bib-<slug> (derived from the bibliography key); cite as [^src-bib-<slug>]. Manual non-bibliography sources continue to use src-NNN.
Iterate on inputs (research_bundle.json), not on the generated output.
Provider+model selection is the user's call — never hardcode.

Composing with research loop

/wiki init reasoning-models --title "Reasoning Models" --flavor research
# Manually compile a research_bundle.json
node skills/survey-generator/scripts/build-survey.js --bundle bundle.json --wiki reasoning-models
# Now the wiki has a structured survey + 50 bibliography rows
# Enable auto-research to expand:
# (edit reasoning-models/wiki.config.md, set auto_research.enabled: true)
node skills/wiki-research-loop/scripts/research-loop.js seed reasoning-models "chain-of-thought failure modes" --depth 0
node skills/wiki-research-loop/scripts/research-loop.js run reasoning-models

FAQ

What does the survey-generator skill do?

How do I install survey-generator?

Run npx skills add https://github.com/rohitg00/pro-workflow --skill survey-generator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/survey-generator/ (personal) or .claude/skills/survey-generator/ (project).

Which AI agents can use survey-generator?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is survey-generator safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains survey-generator?

It is published by rohitg00 in rohitg00/pro-workflow. It has 135 recorded installs.

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survey-generator

Install

Install

Describe the task

Review the result

SKILL.md

Survey Generator

Diff vs dair-academy version

When to use

Inputs

Workflow (the agent runs these in order)

Step 1 — Read the anchor

Step 2 — Build research_bundle.json

Step 3 — Run the generator

Step 4 — Iterate

Output structure

Hard rules

Composing with research loop

FAQ

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