AugmentClaude

Librarium Research

Run research queries across multiple search APIs and deduplicate results.

Installation

  1. Make sure Claude is on your device and in your terminal.

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    One-time setup
    npm i -g @anthropic-ai/claude-code

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When Claude uses it

Run multi-provider deep research queries using the librarium CLI

What this skill does

Librarium -- Multi-Provider Deep Research

Run research queries across 10 search and deep-research APIs in parallel, collect results, deduplicate sources, and produce structured output.

Prerequisites

  • librarium CLI installed (npm install -g librarium)
  • API keys configured (librarium init --auto)
  • Binary at: librarium (or npx librarium)

7-Phase Research Workflow

Phase 1: Query Analysis

Analyze the user's research question. Determine:

  • Is this a technical, business, or general knowledge query?
  • Which provider group is best suited? (quick for fast answers, deep for thorough research, comprehensive for important decisions, all for maximum grounded coverage, llm for an ungrounded baseline/contrast with no citations)
  • What execution mode? (sync for quick queries, mixed for deep research)

Phase 2: Provider Selection

Select providers based on query type:

  • Technical queries: Use comprehensive group (deep research + AI-grounded)
  • Quick facts: Use quick group (AI-grounded only, fast)
  • Competitive research: Use all group (maximum coverage)
  • Specific provider: Use --providers flag (accepts canonical IDs or display names, e.g. -p "Exa Search,brave-search")
  • Competitive research: Use all group (maximum grounded coverage)
  • Ungrounded baseline / contrast: Use llm group (Claude, OpenAI, Gemini, OpenRouter -- direct model answers, no citations)
  • Specific provider: Use --providers flag

Phase 3: Dispatch

Run the query:

librarium run "your query here" --group <group> [--mode mixed]

Phase 4: Monitor Async Tasks

If deep-research providers were used in async mode:

librarium status --wait

Phase 5: Retrieve Results

Once complete, async results can be retrieved:

librarium status --retrieve

Phase 6: Analyze Output

Read the output files:

  1. summary.md -- Overall research summary with statistics
  2. sources.json -- Deduplicated citations ranked by frequency
  3. Individual {provider}.md files for detailed per-provider results
  4. run.json -- Machine-readable manifest

Phase 7: Synthesize

Combine findings from multiple providers into a coherent answer. Cross-reference sources that appear across multiple providers (higher citation count = higher confidence).

Key Commands

CommandPurpose
librarium run <query>Run research query
librarium run <query> --group quickFast AI-grounded search
librarium run <query> --group deepDeep research (async)
librarium run <query> --group allAll providers
librarium answer <query>Fan out (default quick) and synthesize one grounded, cited answer to answer.md
librarium run <query> --max-cost 0.50Stop launching providers once API-reported cost crosses the budget
librarium run <query> --yesSkip the deep-research pre-flight confirm (3+ deep providers)
librarium statusCheck async tasks
librarium status --wait --retrieveWait and fetch async results
librarium usage [--days N] [--json]Aggregate API-reported cost and tokens across past runs
librarium run <query> --html --openRun, then open an HTML report
librarium run <query> --jsonlRun, then write machine-readable results.jsonl
librarium browseBrowse past runs interactively
librarium html [run-dir]Generate report.html for a run
librarium jsonl [run-dir]Generate results.jsonl for a run
librarium refine <goal>Tier-tuned query variants, no dispatch
librarium lsList providers and status
librarium doctorHealth check providers
librarium configShow resolved config
librarium cleanup [--days N] [--dry-run]Delete run dirs older than N days (default 30)
librarium clear [--dry-run] [-i] [--yes]Delete all run dirs (alias for cleanup --all); -i to pick interactively

MCP Server

Instead of shelling out to the CLI, agents can drive librarium over the Model Context Protocol with librarium mcp (stdio transport). Register it once with claude mcp add librarium -- librarium mcp, then call the tools: research, get_results, check_async, list_providers, list_groups. The research tool runs the same silent file-writing pipeline as librarium run and returns a compact structured result; fetch full provider markdown with get_results.

Provider Tiers

TierProvidersSpeedDepth
deep-researchperplexity-sonar-deep, perplexity-deep-research, perplexity-advanced-deep, openai-deep, openai-deep-o3, gemini-deepMinutesComprehensive
ai-groundedperplexity-sonar-pro, brave-answers, exa, you-research, kagi-fastgptSecondsGood
raw-searchperplexity-search, brave-search, jina-search, searchapi, serpapi, tavilyFastLinks only
llmclaude, openai-chat, gemini-chat, openrouter-chatSecondsUngrounded (no citations)

Output Structure

./agents/librarium/{timestamp}-{slug}/
  prompt.md, run.json, summary.md, sources.json
  {provider}.md, {provider}.meta.json
  async-tasks.json (if applicable)

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