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    llm-wiki-maintainer 1.1

    by Roy Yuen

    Turn your AI agent into a digital librarian that builds and audits a persistent markdown knowledge base.

    Updated Jun 2026
    100 views
    Security scanned

    $5

    · or 25 credits

    30-day refund guarantee

    Secure checkout via Stripe

    Included in download

    • Maintain a self-organizing team wiki from raw conversation logs
    • Trace information back to original sources with automated provenance tracking
    • terminal automation included
    • Includes example output and usage patterns
    • Instant install

    See it in action

    A real example of what this skill takes in and produces.

    Sample output

    Updated index.md with 2 new entries. Created decision-record: 'migration-to-fastapi.md' Appended log.md: [2023-10-24] Resolved conflict between source_A and source_B regarding API rate limits. Running wiki_lint.py... 0 orphans found. Wiki is healthy.

    About This Skill

    Maintain a Persistent, Compound Knowledge Base

    The LLM Wiki Maintainer solves the "memory leak" problem in AI workflows where knowledge is lost after a conversation ends. Instead of ephemeral chats, this skill enables your agent to build and maintain a living markdown wiki that grows more valuable over time.

    What it does

    This skill provides a structured framework for an AI agent to act as a librarian and synthesizer. It manages a directory of markdown files using a strict schema, ensuring that raw sources remain immutable while synthesized "knowledge pages" are continuously updated. It handles provenance tracking, contradiction management, and automated indexing.

    Why use this skill

    • Persistence: Every useful answer the AI generates is automatically filed back into the wiki for future use.
    • Provenance: Tracks source hashes and claims so you always know where information came from.
    • Structural Integrity: Includes Python scripts for linting, SQLite-backed indexing, and automated log generation to prevent the wiki from becoming a "junk drawer."
    • Conflict Resolution: Instead of overwriting old data, it reconciles contradictions through dedicated reflection pages.

    Technical Features

    Supports markdown-based folders, SQLite for high-speed querying of page metadata, and custom linting rules for structural health. It works seamlessly with local file systems or cloud-based repositories.

    Use Cases

    • Maintain a self-organizing team wiki from raw conversation logs
    • Trace information back to original sources with automated provenance tracking
    • Reconcile contradictory data points into synthesized decision records
    • Automate the generation of indexes and changelogs for markdown docs

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    Security Scanned

    Passed automated security review

    Permissions

    Terminal / Shell

    Tags

    automation
    data-ingestion
    documentation
    knowledge-management
    markdown
    wiki

    Creator

    Roy Yuen

    Frequently Asked Questions

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