Interactive RLM cache initialization. Use when: setting up a new project's semantic cache for the first time, or adding a new cache profile. Walks the user through folder selection, extension config, manifest creation, and first distillation pass.
Scanned 6/6/2026
Install via CLI
openskills install richfrem/Project_Sanctuary---
name: rlm-init
description: "Interactive RLM cache initialization. Use when: setting up a new project's semantic cache for the first time, or adding a new cache profile. Walks the user through folder selection, extension config, manifest creation, and first distillation pass."
dependencies: ["skill:rlm-curator"]
---
# RLM Init: Cache Bootstrap
Initialize a new RLM semantic cache for any project. This is the **first-run** workflow — run it once per cache, then use `rlm-distill-agent` for ongoing updates.
## When to Use
- First time using RLM Factory in a project
- Adding a new cache profile (e.g., separate cache for API docs vs scripts)
- Rebuilding a cache from scratch after major restructuring
## Examples
Real-world examples of each config file are in `references/examples/`:
| File | Purpose |
|:-----|:--------|
| [`rlm_profiles.json`](../../references/examples/rlm_profiles.json) | Profile registry -- defines named caches and their manifest/cache paths |
| [`rlm_summary_cache_manifest.json`](../../references/examples/rlm_summary_cache_manifest.json) | Project docs manifest -- what folders/globs to include and exclude |
| [`rlm_tools_manifest.json`](../../references/examples/rlm_tools_manifest.json) | Tools manifest -- scoped to scripts and plugins only |
## Interactive Setup Protocol
### Step 1: Ask the User
Before creating anything, gather requirements:
1. **"What do you want cached?"** — What kind of files? (docs, scripts, configs, etc.)
2. **"Which folders should be included?"** — (e.g., `docs/`, `src/`, `plugins/`)
3. **"Which file extensions?"** — (e.g., `.md`, `.py`, `.ts`)
4. **"Where should the cache live?"** — Default: `.agent/learning/` or `config/rlm/`
5. **"What should we name this cache?"** — (e.g., `plugins`, `project`, `tools`)
### Step 2: Configure `rlm_profiles.json`
Each cache is defined as a profile in `rlm_profiles.json`. This file is located at `RLM_PROFILES_PATH` or defaults to `.agent/learning/rlm_profiles.json`. If it doesn't exist, create it:
```bash
mkdir -p <profiles_dir>
```
Create or append to `<profiles_dir>/rlm_profiles.json`:
```json
{
"version": 1,
"default_profile": "<NAME>",
"profiles": {
"<NAME>": {
"description": "<What this cache contains>",
"manifest": "<profiles_dir>/<name>_manifest.json",
"cache": "<profiles_dir>/rlm_<name>_cache.json",
"extensions": [
".md",
".py",
".ts"
]
}
}
}
```
| Key | Purpose |
|----------|---------|
| `description` | Human-readable explanation of the profile's purpose |
| `manifest` | Path to the manifest JSON (what folders/files to index) |
| `cache` | Path to the cache JSON (where summaries are stored) |
| `extensions` | List of string file extensions to include |
### Step 3: Create the Manifest
The manifest defines **which folders, files, and globs** to index. Extensions come from the profile config.
Create `<manifest_path>`:
```json
{
"description": "<What this cache contains>",
"include": [
"<folder_or_glob_1>",
"<folder_or_glob_2>"
],
"exclude": [
".git/",
"node_modules/",
".venv/",
"__pycache__/"
],
"recursive": true
}
```
### Step 4: Initialize Empty Cache
```bash
echo "{}" > <cache_path>
```
### Step 5: Audit (Show What Needs Caching)
Scan the manifest against the cache to find uncached files:
```bash
python3 ./scripts/inventory.py --profile <NAME>
```
Report: "N files in manifest, M already cached, K remaining."
### Step 6: Serial Agent Distillation
For each uncached file:
1. **Read** the file
2. **Summarize** — Generate a concise, information-dense summary
3. **Write** the summary into the cache JSON with this schema:
```json
{
"<relative_path>": {
"hash": "agent_distilled_<YYYY_MM_DD>",
"summary": "<your summary>",
"summarized_at": "<ISO timestamp>"
}
}
```
4. **Log**: `"✅ Cached: <path>"`
5. **Repeat** for next file
### Step 7: Verify
Run audit again:
```bash
python3 ./scripts/inventory.py --profile <NAME>
```
Target: 100% coverage. If gaps remain, repeat Step 6 for missing files.
## Quality Guidelines
Every summary should answer: **"Why does this file exist and what does it do?"**
| ❌ Bad | ✅ Good |
|--------|---------|
| "This is a README file" | "Plugin providing 5 composable agent loop patterns for learning, red team review, dual-loop delegation, and parallel swarm execution" |
| "Contains a SKILL definition" | "Orchestrator skill that routes tasks to the correct loop pattern using a 4-question decision tree, manages shared closure sequence" |
## After Init
- Use [`rlm-distill-agent`](../rlm-distill-agent/SKILL.md) for ongoing cache updates
- Use [`rlm-curator`](../rlm-curator/SKILL.md) for querying, auditing, and cleanup
- Cache files should be `.gitignore`d if they contain project-specific summaries
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