openclaw-llm-wikiCreate and maintain a persistent LLM-maintained knowledge base (wiki) following Andrej Karpathy's pattern. The LLM actively builds and maintains interconnect...
Install via ClawdBot CLI:
clawdbot install pathanaawej0-dot/openclaw-llm-wikiGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Generated Oct 6, 2026
An independent researcher or PhD student uses the LLM Wiki to ingest papers, articles, and notes, letting the agent synthesize findings into interconnected concept and entity pages. Over time, the wiki becomes a second brain that compounds knowledge and surfaces contradictions or gaps. Queries are answered with citations and can be filed back as new pages.
A strategy team continuously adds competitor reports, press releases, and analyst notes to the raw folder. The LLM Wiki maintains entity pages for each competitor, tracks changes over time, and flags stale claims. Executives can ask natural language questions and receive synthesized, cited answers without re-reading source documents.
A software engineering team uses the wiki to capture design decisions, incident postmortems, and architectural concepts. The agent cross-references entities like services and libraries, detects orphan pages, and suggests missing cross-links. New engineers query the wiki to quickly understand system evolution and rationale.
A clinical quality team ingests medical guidelines, drug interaction studies, and internal protocols. The LLM Wiki builds concept pages for treatments and entity pages for drugs, maintaining a consistent, auditable knowledge base. Clinicians query it for evidence-based answers, and the system flags contradictions between sources for human review.
A law firm maintains a wiki of case summaries, legal concepts, and judge profiles. The agent ingests new rulings, updates relevant concept pages, and cross-references precedents. Lawyers query the wiki to quickly find relevant cases and understand how new decisions affect existing interpretations, with all updates logged.
The LLM Wiki skill is released as open-source under a permissive license, driving adoption among individuals and small teams. A commercial entity offers paid enterprise support, including custom SCHEMA.md configuration, integration with existing knowledge systems, and priority bug fixes. Revenue comes from annual support contracts and consulting services.
A cloud service hosts the LLM Wiki infrastructure, handling file storage, version control, and model API costs. Users interact via a web interface or API, paying a monthly subscription based on storage and query volume. The platform adds collaboration features, audit logs, and enterprise SSO.
The core technology is licensed to vertical SaaS providers (e.g., in healthcare or legal tech) who embed it as a knowledge management module. These partners pay a licensing fee per seat or per installation, and the original creators provide integration support and updates. Revenue is generated through B2B licensing deals.
💬 Integration Tip
Start by configuring SCHEMA.md to match your domain's naming conventions and desired output format; the skill works with any LLM that has file system access, but for best results use an agent that maintains context across sessions. Integrate with version control (e.g., git) to track changes and enable collaboration.
Scored Oct 6, 2026
Manage a personal knowledge base by adding, searching, organizing, and reviewing articles, links, and notes with tags and natural language queries.
Generate a daily work report by automatically discovering all git repositories the user worked on, collecting commit logs across all branches, and summarizin...
日记引导助手。每日写作引导、感恩日记、反思日记、晨间日记、晚间总结、周总结模板。Journal prompts for daily writing, gratitude, reflection, morning pages, evening review, weekly summary. 日记、写作、反思、感恩。
Use when maintaining RDR2 (Red Dead Redemption 2) playthrough notes — logging an acquisition ("acquired X", "got N gold bars", "finished X"), answering in-game location/crafting questions, or reviewing the notes for duplicate or stale info. Triggers on RDR2, Red Dead Redemption, playthrough, legendary animal, talisman, trinket, valerian root, gold bar, horse, weapon, berry.
Use when a sales rep already has a customer who has expressed some need (from outreach follow-up, account-landing research, customer-initiated contact, or meeting notes) and needs to structurally validate whether that need is real, urgent, whose pain it actually is, and whether it matches the team's capability — before pushing to ROI proofing or buying-intent assessment. Triggers: '验证一下这个需求是不是真的', '需求真不真', '客户说痛但我不确定', '这个客户值不值得跟', '客户说会考虑但是真的吗', '谁拍板', '现有方案是什么', '切换成本', 'need validation', 'pain point validation', 'is this a real need', 'verify customer need'. Do NOT use for: scoring leads at line-item level, building target-customer profiles, calculating ROI, overall buying-intent scoring, opportunity-stage assessment, or writing outreach/cold messages.
Microsoft OneNote integration. Manage Notebooks. Use when the user wants to interact with Microsoft OneNote data.