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This is the documentation for v3.2.0. The current major version is v4. v4 removes the Paperclip integration and adds an optional hosted wiki. Read the upgrade guide, or go to the current documentation.

Upgrade to v3.2.0 ​

v3.2.0 adds optional experience capture and evaluated skill improvements. It is a minor release because existing wikis, frontmatter and CLI flags remain compatible. It does not enable a background optimizer.

Update the installed plugin/skill, then run /wiki:upgrade against your configured wiki. The existing runtime setup remains mandatory. Upgrade adds .experience-template.json, .pattern-template.md and .evolution/README.md only if absent; custom files and SCHEMA.md are preserved. It proposes an optional ## Skill evolution schema section for review.

Use /wiki:learn for verified task experience, then /wiki:evolve for evidence-linked proposals and measured promotion. No evaluation or skill replacement occurs during upgrade. Back up .evolution/ as durable history, unlike the disposable .wiki-cache/. See Learning and skill evolution for the runner contract, pilot suite, inference budgets and rollback.

The Paperclip companion v0.5.3 excludes experiment snapshots from its browse/search/health surfaces. Update that companion separately when using it with an evolving wiki.

Upgrading from before v3.0 ​

v3.0.0 replaces provider-backed embeddings with default local FastEmbed + sqlite-vec retrieval. Existing Markdown stays untouched; only the disposable vector index changes.

No content migration

No page or frontmatter format changed. The old embeddings.jsonl cache is ignored and can be deleted; /wiki:upgrade builds embeddings.sqlite locally and synchronizes every current section.

Why it's a major version ​

The default section search now initializes a local model and sqlite-vec index instead of staying lexical unless a provider is configured. The data boundary becomes strictly local and the old provider environment variables and approval flag are removed. Direct python wiki_search.py "<query>" --no-embed preserves dependency-free BM25.

The upgrade ​

  1. Pull the current release. Update the plugin the same way you installed it: for Claude Code, re-run the marketplace install; for skill-only agents, re-run npx skills add.

  2. Run the upgrade. In Claude Code:

    bash
    /wiki:upgrade

    Or directly, pass the installed script and the selected base directory separately. For a project wiki:

    bash
    python "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/init_wiki.py" "<absolute-project-root>" --upgrade

    For the standard personal global layout:

    bash
    python "${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki/scripts/init_wiki.py" "<absolute-home-directory>" --wiki-dir wiki --raw-dir wiki/raw --upgrade

    For a skill-only install, replace ${CLAUDE_PLUGIN_ROOT}/skills/llm-wiki with that agent's installed llm-wiki skill directory. Never use the plugin or skill directory as the base directory.

    Expected: Idempotent file operations leave existing pages untouched. Runtime setup then reports "status": "ready" with pinned dependency versions, model, page count, section count, and vector-index path before the command reports the missing SCHEMA marker.

  3. Approve the SCHEMA.md merge. Add the local semantic backend lines from the current template to your existing ## Retrieval section. SCHEMA.md is co-evolved with you and is never modified silently.

Re-running the upgrade is idempotent: existing content stays unchanged, dependencies/model are verified, and only changed or missing vectors are embedded.

What changes for you ​

  • Existing pages need no changes. Nothing canonical under wiki/ is rewritten.
  • Section search is local hybrid by default. FastEmbed + sqlite-vec semantic ranking is fused with BM25. Run the script directly with Python and --no-embed for dependency-free lexical retrieval, or use --granularity page for whole-page ranking.
  • Upgrade installs everything. The command resolves pinned FastEmbed, sqlite-vec, and PyYAML packages through uv, downloads the pinned model if absent, builds the parse cache, and embeds all current sections.
  • wiki/.wiki-cache/ is regenerable. search-index.json and embeddings.sqlite are gitignored and safe to delete. Legacy embeddings.jsonl is ignored.
  • No provider setup remains. No API key, endpoint, data-transfer approval, or per-query charge is involved.

WARNING

No wiki yet? There's nothing to upgrade. Run /wiki:init instead.

Released under the MIT License.