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Local-first multimedia research library for hardware projects. Capture code, CAD, PDFs, images. Search with material-type weighting. Project isolation with cross-references. Async extraction. Backup + restore.
デフォルトでは、最初にソースを確認する Prompt が選択されています。直接コマンドに切り替えるか、ローカルコピーをダウンロードすることもできます。
インストールを決める前に、SKILL.md と SkillsMP に表示されている付属ファイルをお読みください。
SOC 職業分類に基づく
Codex または Claude でインストール この Prompt をコピーして Codex、Claude、または他のアシスタントに貼り付けると、Skill ページを確認してインストールできます。
直接コマンドでは確認用 Prompt が省略されます。実行前にソースを確認してください。
npx skills add https://github.com/javimosch/open-claw-skills --skill research-libraryコマンドは1行のまま表示されます。コピー前に横へスクロールして全体を確認してください。
ローカルで確認しますか？SkillsMP が現在取得できるファイルをダウンロードできます。
SKILL.md を表示中
Connect your AI assistant to GoHighLevel CRM via the official API v2. Manage contacts, conversations, calendars, pipelines, invoices, payments, workflows, and 30+ endpoint groups through natural language. Includes interactive setup wizard and 100+ pre-built, safe API commands. Python 3.6+ stdlib only — zero external dependencies.
Manage Cloudflare DNS records, Tunnels (cloudflared), and Zero Trust policies. Use for pointing domains, exposing local services via tunnels, and updating ingress rules.
Mema's personal brain - SQLite metadata index for documents and Redis short-term context buffer. Use for organizing workspace knowledge paths and managing ephemeral session state.
| name | research-library |
| description | Local-first multimedia research library for hardware projects. Capture code, CAD, PDFs, images. Search with material-type weighting. Project isolation with cross-references. Async extraction. Backup + restore. |
| version | 0.1.0 |
| author | Sage (for Jon Buckles) |
| license | MIT |
| tags | ["knowledge-management","research","hardware","documentation","sqlite","fts5"] |
| repository | https://github.com/[user]/research-library |
| keywords | ["library","search","extraction","project-management","knowledge-base"] |
A local-first multimedia research library for capturing, organizing, and searching hardware project knowledge.
clawhub install research-library
# OR
pip install /path/to/research-library
# 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
reslib add — Import documents (auto-detect + extract)reslib search — Full-text search with filtersreslib get — View document detailsreslib archive / reslib unarchive — Manage documentsreslib export — Export as JSON/Markdownreslib link — Create document relationshipsreslib projects — Manage projectsreslib tags — Manage tagsreslib status — System overviewreslib backup / reslib restore — Snapshotsreslib smoke_test.sh — Quick validationCopy reslib/config.json and customize:
{
"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
}
Use RL1 protocol in war room DNA:
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="...", ...)
All targets exceeded:
| Operation | Target | Actual |
|---|---|---|
| PDF extraction | <100ms | 20.6ms |
| Search (50 docs) | <100ms | 0.33ms |
| Worker throughput | >6/sec | 414.69/sec |
# Run all tests
pytest tests/
# Quick smoke test
bash reslib/smoke_test.sh
# Performance tests
pytest tests/test_integration.py -v -k stress
See /docs/:
CLI-REFERENCE.md — All commands + examplesEXTRACTION-GUIDE.md — How extraction worksSEARCH-GUIDE.md — Ranking + weightingWORKER-GUIDE.md — Async queue detailsINTEGRATION.md — War room RL1 protocolcd research-library
pip install -e .
pytest tests/
python -m reslib status
Issues? See TECHNICAL-NOTES.md for troubleshooting.
Production-ready MVP. 214 tests passing. 15K lines. Ready to use.