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Research Library

Local-first multimedia research library for hardware projects.

Rating
4.7 (349 reviews)
Downloads
1,412 downloads
Version
1.0.0

Overview

Local-first multimedia research library for hardware projects.

✨Key Features

1

Store documents — Code, PDFs, CAD files, images, schematics

2

Extract automatically — Text from PDFs, EXIF from images, functions from code

3

Search intelligently — Full-text with material-type weighting (your work ranks higher than external research)

4

Project isolation — Arduino separate from CNC; no contamination

5

Cross-reference — Link knowledge: "this servo tuning applies to that project"

6

Async extraction — Searches never block while OCR runs

7

Backup daily — 30-day rolling snapshots

Complete Documentation

View Source →

Research Library Skill

A local-first multimedia research library for capturing, organizing, and searching hardware project knowledge.

What It Does

  • Store documents — Code, PDFs, CAD files, images, schematics
  • Extract automatically — Text from PDFs, EXIF from images, functions from code
  • Search intelligently — Full-text with material-type weighting (your work ranks higher than external research)
  • Project isolation — Arduino separate from CNC; no contamination
  • Cross-reference — Link knowledge: "this servo tuning applies to that project"
  • Async extraction — Searches never block while OCR runs
  • Backup daily — 30-day rolling snapshots

Installation

bash
clawhub install research-library
# OR
pip install /path/to/research-library

Quick Start

bash
# Initialize database
reslib status

# Add a project
reslib add ~/projects/arduino/servo.py --project arduino --material-type reference

# Search
reslib search "servo tuning"

# Link knowledge
reslib link 5 12 --type applies_to

Features

CLI Commands

  • reslib add — Import documents (auto-detect + extract)
  • reslib search — Full-text search with filters
  • reslib get — View document details
  • reslib archive / reslib unarchive — Manage documents
  • reslib export — Export as JSON/Markdown
  • reslib link — Create document relationships
  • reslib projects — Manage projects
  • reslib tags — Manage tags
  • reslib status — System overview
  • reslib backup / reslib restore — Snapshots
  • reslib smoke_test.sh — Quick validation

Technical

  • Storage: SQLite 3.45+ with FTS5 virtual table
  • Extraction: PDF (pdfplumber + OCR), images (EXIF + OCR), code (AST + regex)
  • Confidence Scoring: 0.0-1.0 based on quality + source
  • Material Weighting: Reference (1.0) vs Research (0.5)
  • Project Isolation: Scoped searches, no contamination
  • Async Workers: 2-4 configurable extraction workers
  • Catalog Separation: real_world vs openclaw projects
  • Backup: Daily snapshots, 30-day retention

Configuration

Copy reslib/config.json and customize:

json
{
  "db_path": "~/.openclaw/research/library.db",
  "num_workers": 2,
  "worker_timeout_sec": 300,
  "max_retries": 3,
  "backup_retention_days": 30,
  "backup_dir": "~/.openclaw/research/backups",
  "file_size_limit_mb": 200,
  "project_size_limit_gb": 2
}

Integration with War Room

Use RL1 protocol in war room DNA:

python
from reslib import ResearchDatabase, ResearchSearch

db = ResearchDatabase()
search = ResearchSearch(db)

# Before researching, check existing knowledge
prior = search.search("servo tuning", project="rc-quadcopter")
if prior:
    print(f"Found {len(prior)} prior items")
else:
    # New research needed...
    db.add_research(title="...", content="...", ...)

Performance

All targets exceeded:

OperationTargetActual
PDF extraction<100ms20.6ms
Search (50 docs)<100ms0.33ms
Worker throughput>6/sec414.69/sec

Testing

bash
# Run all tests
pytest tests/

# Quick smoke test
bash reslib/smoke_test.sh

# Performance tests
pytest tests/test_integration.py -v -k stress

Known Limitations (Phase 2)

  • OCR quality varies on hand-drawn sketches
  • FTS5 designed for <10K documents (PostgreSQL path for scale)
  • No automatic web research gathering (manual only)
  • Vector embeddings ready but inactive
  • CAD file parsing is metadata-only

Documentation

See /docs/:

  • CLI-REFERENCE.md — All commands + examples
  • EXTRACTION-GUIDE.md — How extraction works
  • SEARCH-GUIDE.md — Ranking + weighting
  • WORKER-GUIDE.md — Async queue details
  • INTEGRATION.md — War room RL1 protocol

Phase 2 Roadmap

  • Real-world PDF calibration
  • FTS5 scaling tests (10K docs)
  • Auto-detection (reference vs research)
  • Web research enrichment
  • Vector embeddings (semantic search)
  • PostgreSQL upgrade path

Building From Source

bash
cd research-library
pip install -e .
pytest tests/
python -m reslib status

Support

Issues? See TECHNICAL-NOTES.md for troubleshooting.

Production-ready MVP. 214 tests passing. 15K lines. Ready to use.

Installation

Terminal bash 

openclaw install research-library
Copied!

💻Code Examples

reslib link 5 12 --type applies_to

reslib-link-5-12---type-appliesto.txt
## Features

### CLI Commands
- `reslib add` — Import documents (auto-detect + extract)
- `reslib search` — Full-text search with filters
- `reslib get` — View document details
- `reslib archive` / `reslib unarchive` — Manage documents
- `reslib export` — Export as JSON/Markdown
- `reslib link` — Create document relationships
- `reslib projects` — Manage projects
- `reslib tags` — Manage tags
- `reslib status` — System overview
- `reslib backup` / `reslib restore` — Snapshots
- `reslib smoke_test.sh` — Quick validation

### Technical
- **Storage:** SQLite 3.45+ with FTS5 virtual table
- **Extraction:** PDF (pdfplumber + OCR), images (EXIF + OCR), code (AST + regex)
- **Confidence Scoring:** 0.0-1.0 based on quality + source
- **Material Weighting:** Reference (1.0) vs Research (0.5)
- **Project Isolation:** Scoped searches, no contamination
- **Async Workers:** 2-4 configurable extraction workers
- **Catalog Separation:** real_world vs openclaw projects
- **Backup:** Daily snapshots, 30-day retention

## Configuration

Copy `reslib/config.json` and customize:

}

.txt
## Integration with War Room

Use RL1 protocol in war room DNA:

db.add_research(title="...", content="...", ...)

-dbaddresearchtitle-content-.txt
## Performance

All targets exceeded:

| Operation | Target | Actual |
|-----------|--------|--------|
| PDF extraction | <100ms | 20.6ms |
| Search (50 docs) | <100ms | 0.33ms |
| Worker throughput | >6/sec | 414.69/sec |

## Testing

pytest tests/test_integration.py -v -k stress

pytest-teststestintegrationpy--v--k-stress.txt
## Known Limitations (Phase 2)

- OCR quality varies on hand-drawn sketches
- FTS5 designed for <10K documents (PostgreSQL path for scale)
- No automatic web research gathering (manual only)
- Vector embeddings ready but inactive
- CAD file parsing is metadata-only

## Documentation

See `/docs/`:
- `CLI-REFERENCE.md` — All commands + examples
- `EXTRACTION-GUIDE.md` — How extraction works
- `SEARCH-GUIDE.md` — Ranking + weighting
- `WORKER-GUIDE.md` — Async queue details
- `INTEGRATION.md` — War room RL1 protocol

## Phase 2 Roadmap

- Real-world PDF calibration
- FTS5 scaling tests (10K docs)
- Auto-detection (reference vs research)
- Web research enrichment
- Vector embeddings (semantic search)
- PostgreSQL upgrade path

## Building From Source
example.sh
clawhub install research-library
# OR
pip install /path/to/research-library
example.sh
# Initialize database
reslib status

# Add a project
reslib add ~/projects/arduino/servo.py --project arduino --material-type reference

# Search
reslib search "servo tuning"

# Link knowledge
reslib link 5 12 --type applies_to
example.json
{
  "db_path": "~/.openclaw/research/library.db",
  "num_workers": 2,
  "worker_timeout_sec": 300,
  "max_retries": 3,
  "backup_retention_days": 30,
  "backup_dir": "~/.openclaw/research/backups",
  "file_size_limit_mb": 200,
  "project_size_limit_gb": 2
}
example.py
from reslib import ResearchDatabase, ResearchSearch

db = ResearchDatabase()
search = ResearchSearch(db)

# Before researching, check existing knowledge
prior = search.search("servo tuning", project="rc-quadcopter")
if prior:
    print(f"Found {len(prior)} prior items")
else:
    # New research needed...
    db.add_research(title="...", content="...", ...)
example.sh
# Run all tests
pytest tests/

# Quick smoke test
bash reslib/smoke_test.sh

# Performance tests
pytest tests/test_integration.py -v -k stress
example.sh
cd research-library
pip install -e .
pytest tests/
python -m reslib status

Tags

#image_and-video-generation

Quick Info

Category Content Creation
Model Claude 3.5
Complexity One-Click
Author jonbuckles
Last Updated 3/10/2026
🚀
Optimized for
Claude 3.5
🧠

Ready to Install?

Get started with this skill in seconds

openclaw install research-library

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