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Obsidian rlm distiller

Skill richfrem/agent-plugins-skills/plugins/obsidian-wiki-engine/skills/obsidian-rlm-distiller

Distills wiki source files into the RLM summary layer (summary.md, bullets.md, deep.md) using the cheapest available LLM CLI. Routes to Copilot gpt-5-mini first, then Claude Haiku, then Gemini Flash. Never uses Ollama. Use when wiki nodes need RLM summaries generated or refreshed.From its SKILL.md

Install
npx -y skills add richfrem/agent-plugins-skills --skill obsidian-rlm-distiller

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SKILL.md

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Dependencies

Requires Python 3.8+ and at least one CLI installed: copilot, claude, or gemini.

pip install -r requirements.txt

Obsidian RLM Distiller

Status: Active Author: Richard Fremmerlid Domain: Obsidian Wiki Engine Replaces: rlm-distill-ollama (fully deprecated)

Purpose

Distills registered wiki source files into the three-layer RLM summary structure inside {wiki_root}/rlm/{concept}/. Delegates work to the cheapest available LLM CLI — never a local Ollama server.

Cheap-Model Fallback Chain (Strict)

1. copilot CLI available?  → use gpt-5-mini        (fastest, Paid - AI Credits)
2. claude CLI available?   → use claude-haiku-4-5  (fallback, Paid)
3. gemini CLI available?   → use gemini-3-flash-preview (final fallback, Paid)
4. none found              → exit with instructions

rlm-distill-ollama is fully deprecated. Only rlm-distill-agent pointing at cheap cloud models is supported.

Output: Three-Layer RLM Structure

{wiki_root}/rlm/{concept}/
  summary.md    ← 1-5 sentence distilled summary
  bullets.md    ← key idea bullets (6-10 points)
  deep.md       ← full multi-pass distillation

Usage

Distill all stale wiki nodes

python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root

Distill one named source

python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root --source arch-docs

Force engine override

python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root --engine claude
python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root --engine gemini
python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root --engine copilot

Use shared .agent/learning/ cache (colocates with rlm-factory)

python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root \
    --rlm-cache-dir /path/to/project/.agent/learning/rlm_wiki_cache

Dry run

python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root --dry-run

Engine Detection Logic

distill_wiki.py calls shutil.which() for each CLI in priority order. The first one found and authenticated is used for the entire batch:

ENGINE_PRIORITY = [
    ("copilot", "gpt-5-mini"),
    ("claude",  "claude-haiku-4-5"),
    ("gemini",  "gemini-3-flash-preview"),
]

RLM Cache Storage

distill_wiki.py writes summaries directly into its own RLM cache directory. No cross-plugin script calls are made (ADR-001 compliant).

Default cache: {wiki-root}/rlm/{concept}/

To colocate with rlm-factory under .agent/learning/, pass --rlm-cache-dir:

python ./scripts/distill_wiki.py --wiki-root /path/to/wiki-root \
    --rlm-cache-dir /path/to/project/.agent/learning/rlm_wiki_cache

The cache location is determined by configuration in .agent/learning/rlm_profiles.json (the cache key of the wiki profile) — not by hard-coded cross-plugin paths.

When to Use

  • After /wiki-ingest populates new wiki nodes
  • When RLM summaries are missing or stale
  • Before running /wiki-query for optimal recall
  • As part of the /wiki-rebuild full pipeline

Related Scripts

  • distill_wiki.py — cheap-model fallback orchestrator
  • raw_manifest.pyWikiSourceConfig loader
  • audit.py — identifies stale/missing RLM summaries

What ships with it: 5 files

786 B alongside SKILL.md, 3 of them executable

evals/

scripts/

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