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modeled-information-formatmodeled-information-format/mnemonic/skills/qmd-setup/SKILL.md

qmd-setup

Skill23 starsChanged 10 months agoMITView on GitHub

Set up @tobilu/qmd semantic search for mnemonic memories. Registers collections, builds indexes, and generates embeddings. Run this once per machine.

  • Installs packages

The file

We split this skill into the rules it gives an agent

5 rules. About 0 are common, 2 are distinctive, and 3 are very specific to this project.

  • ≈0

    Common · estimate

    Many files like this have a rule of this kind.

  • ≈2

    Distinctive · estimate

    This author's own choices. Worth a look.

  • 3

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Distinctive:

    Run the setup script:

    line 22
  2. Very specific:

    Check prerequisites (Node.js >= 22, qmd installed)

    line 29
  3. Very specific:

    Run qmd update (index) + qmd embed (embeddings)

    line 35
  4. Distinctive:

    If you prefer to set up manually:

    line 42
  5. Very specific:

    After adding new memories, re-index with /mnemonic:qmd-reindex or:

    line 84

≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

QMD Setup Skill

Bootstrap @tobilu/qmd for semantic search over mnemonic memories.

Prerequisites

  • Node.js >= 22 — node --version
  • qmd CLI — npm i -g @tobilu/qmd

Automated Setup

Run the setup script:

bash tools/qmd-setup.sh

The script will:

  1. Check prerequisites (Node.js >= 22, qmd installed)
  2. Resolve MNEMONIC_ROOT from ~/.config/mnemonic/config.json
  3. Discover memory roots dynamically:
    • {MNEMONIC_ROOT}/{org}/ → collection mnemonic-{org}
    • {MNEMONIC_ROOT}/default/ → collection mnemonic-default
    • .claude/mnemonic/ → collection mnemonic-project
  4. Run qmd update (index) + qmd embed (embeddings)
  5. Validate with qmd status and a test search

Note: First qmd embed downloads ~2 GB of GGUF models.

Manual Setup

If you prefer to set up manually:

MNEMONIC_ROOT is resolved from ~/.config/mnemonic/config.json (defaults to ~/.local/share/mnemonic). Adjust the paths below to match your config:

# 1. Register collections (replace paths with your MNEMONIC_ROOT)
qmd collection add "${MNEMONIC_ROOT:-$HOME/.local/share/mnemonic}/zircote/" --name mnemonic-zircote
qmd collection add "${MNEMONIC_ROOT:-$HOME/.local/share/mnemonic}/default/" --name mnemonic-default
qmd collection add "$(git rev-parse --show-toplevel)/.claude/mnemonic/" --name mnemonic-project  # if exists

# 2. Build index
qmd update

# 3. Generate embeddings (downloads models on first run)
qmd embed

# 4. Validate
qmd status
qmd search "test" -n 3

After Setup

Use search commands:

CommandTypeRequires
qmd search "query"BM25 keywordqmd update
qmd vsearch "query"Semantic vectorqmd embed
qmd query "query"Hybrid (BM25 + vector)Both

Scope to a specific collection:

qmd search "auth" -c mnemonic-zircote    # org memories only
qmd search "auth" -c mnemonic-project    # this repo only
qmd search "auth"                        # all collections

Re-indexing

After adding new memories, re-index with /mnemonic:qmd-reindex or:

qmd update && qmd embed

Indexing is not automatic — run after captures or bulk imports.

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