hermes-skills/ai-brain-kb/SKILL.md

---
name: ai-brain-kb
description: "Manage the ai_brain_kb Qdrant collection — add documents, search, and remove. Central knowledge base for all AI/ML learnings, pipeline details, and research."
version: 1.0.0
author: Hermes Agent
license: MIT
platforms: [linux]
metadata:
  hermes:
    tags: [qdrant, knowledge-base, ai-brain, search, rag]
    related_skills: [save-q-memory, qdrant-collection-management]
---

# AI Brain KB — Qdrant Knowledge Base Manager

Manage the `ai_brain_kb` Qdrant collection — the central knowledge base for all AI/ML learnings, pipeline details, research, and decisions.

## Storage Location

| Setting | Value |
|---------|-------|
| Qdrant | http://10.0.0.22:6333 |
| Collection | `ai_brain_kb` |
| Embedding | Ollama (snowflake-arctic-embed2) |
| MCP Tool | `mcp__better_qdrant__*` |

## What Goes Here

Everything AI/ML related that should be searchable across sessions:

- Pipeline plans, state, and architecture decisions
- Story prompts and scene descriptions
- Research results (deep research, better-search outputs)
- Model configurations, LoRA chains, render settings
- Bug diagnoses and fixes
- Stock material research
- Prompt engineering guides
- Hardware/infrastructure details for AI workloads

## Commands

### Add Documents

Add a file (markdown, text, JSON) to the knowledge base. The file is chunked and embedded automatically.

```
mcp__better_qdrant__add_documents(
  collection="ai_brain_kb",
  embeddingService="ollama",
  filePath="/absolute/path/to/file.md"
)
```

**Chunking:** Default 500 chars with 50 char overlap. Works for .md, .txt, .json, .py files.

**After adding:** Confirm chunk count to user.

### Search

Semantic search across all knowledge in the collection.

```
mcp__better_qdrant__search(
  collection="ai_brain_kb",
  embeddingService="ollama",
  query="your search query",
  limit=10
)
```

**Tips:**
- Use natural language queries — "LTX artifact causes" not "ltx artifact"
- Results include score, title, URL (if applicable), summary, and key claims
- Higher limit = more context but more tokens

### Remove Documents

Delete individual documents by their source path (if tracked) or delete the entire collection and rebuild.

**Remove entire collection (nuclear option):**
```
mcp__better_qdrant__delete_collection(collection="ai_brain_kb")
```

**Note:** There is no per-document delete in the current MCP tool. To remove specific content, delete the collection and re-add only the files you want to keep.

### List All Collections

See what collections exist on the Qdrant instance:

```
mcp__better_qdrant__list_collections()
```

## Workflow: Save Session Learnings

After a significant session (new research, bug fix, pipeline change):

1. **Identify new/changed files** — what markdown docs were created or updated?
2. **Add to ai_brain_kb** — use `add_documents` for each file
3. **Confirm** — report chunk counts to user
4. **Clean up** — if old topic-specific collections exist, merge and delete them

## Workflow: Research a Topic

When starting work on an AI/ML topic:

1. **Search ai_brain_kb first** — what do we already know?
2. **If gaps found** — dispatch deep-research or better-search
3. **Save results** — add the research output file to ai_brain_kb
4. **Proceed** — now you have full context

## Pitfalls

- **File paths must be absolute** — the MCP tool resolves from the Hermes host filesystem.
- **Large files chunk automatically** — 500 char chunks. Very large files (100K+ chars) may produce many chunks; consider summarizing first.
- **No per-document delete** — the MCP tool only supports collection-level delete. Plan your adds accordingly.
- **Embedding model must be running** — Ollama with `snowflake-arctic-embed2` must be available on the Qdrant host (10.0.0.22:11434).
- **Collection name is exact** — `ai_brain_kb`, not `ai-brain-kb` or `ai_brain`.
- **Search is semantic, not keyword** — phrase queries naturally. "How to fix LTX artifacts" works better than "ltx artifact fix".
- **Don't create topic-specific collections** — everything goes into `ai_brain_kb`. The user's rule: one brain, one collection.

## Related Skills

- `save-q-memory` — Manual save to the `memories` collection (personal/behavioral memory, not knowledge base)
- `qdrant-collection-management` — Collection-level operations: consolidation, migration, dedup, registry