hermes-skills/ltx23-kb/SKILL.md

name, description, version, author, license, platforms, metadata

name	description	version	author	license	platforms	metadata
ltx23-kb	Manage the ltx23_kb Qdrant collection for LTX 2.3 knowledge.	1.0.0	Hermes Agent	MIT	linux	hermes tags related_skills qdrant knowledge-base ltx video ltx23 ai-brain-kb qdrant-collection-management ltx-video-pipeline

LTX 2.3 Knowledge Base — Qdrant Collection Manager

Manage the ltx23_kb Qdrant collection — the dedicated knowledge base for LTX 2.3 video generation. Tracks known issues, resolutions, prompt suggestions, new modules, official source updates, and community findings.

Storage Location

Setting	Value
Qdrant	http://10.0.0.22:6333
Collection	ltx23_kb
Dimensions	1024
Distance	Cosine
Embedding	Ollama (snowflake-arctic-embed2)
MCP Tool	mcp__better_qdrant__*

What Goes Here

Everything LTX 2.3 related that should be searchable across sessions:

• Known issues — bugs, artifacts, model limitations, workarounds
• Resolutions — fixes, patches, config changes that solved problems
• Prompt suggestions — effective prompt patterns, structures, word limits
• New modules — community modules, extensions, LoRAs, pipelines
• Official source tracking — Lightricks GitHub releases, changelogs, docs
• Community findings — HuggingFace discussions, Reddit, Discord insights
• Render settings — proven configs (steps, guidance, resolution, CFG)
• Pipeline decisions — architecture choices, model chain wiring

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="ltx23_kb",
  embeddingService="ollama",
  filePath="/absolute/path/to/file.md"
)

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

Search

Semantic search across all LTX 2.3 knowledge.

mcp__better_qdrant__search(
  collection="ltx23_kb",
  embeddingService="ollama",
  query="your search query",
  limit=10
)

Tips:

• Use natural language queries — "LTX 2.3 temporal consistency fix" not "ltx artifact"
• Results include score, title, summary, and key claims
• Higher limit = more context but more tokens

List All Collections

mcp__better_qdrant__list_collections()

Workflow: Save Research Findings

After researching LTX 2.3 (new release, bug fix, community finding):

1. Write findings to a markdown file in ~/workspace/general/ or a dedicated LTX workspace
2. Add to ltx23_kb — use add_documents for the file
3. Confirm — report chunk count to user
4. Cross-reference — search ai_brain_kb and local-ai-video-research for related context

Workflow: Research an LTX Issue

When troubleshooting or exploring LTX 2.3:

1. Search ltx23_kb first — what do we already know?
2. Search ai_brain_kb — broader AI video context
3. If gaps found — dispatch web search for official sources (Lightricks GitHub, HuggingFace)
4. Save results — add the research output to ltx23_kb
5. Proceed — now you have full context

Official Sources

Primary sources to monitor (for cron-based updates):

• GitHub: https://github.com/Lightricks/LTX-Video — official repo, releases, issues
• HuggingFace: https://huggingface.co/Lightricks/LTX-Video — model weights, model cards
• HuggingFace Community: https://huggingface.co/Lightricks — organization page

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 at 10.0.0.30:11434 (mini).
• Collection name is exact — ltx23_kb, not ltx-23-kb or ltx23.
• Search is semantic, not keyword — phrase queries naturally. "How to fix LTX temporal artifacts" works better than "ltx artifact fix".
• Don't mix with ai_brain_kb — ltx23_kb is scoped to LTX 2.3 specifically. Broader AI video knowledge goes to ai_brain_kb.
• Prompt ceiling — LTX 2.3 official limit is 200 words (Lightricks GitHub README). Community extends to 150-300 words for 10s clips. One main action per 2-3 seconds of video.

Related Skills

• ai-brain-kb — Central AI/ML knowledge base (broader scope)
• qdrant-collection-management — Collection-level operations: consolidation, migration, dedup, registry
• ltx-video-pipeline — LTX Video pipeline on 10.0.0.202
• local-ai-media-generation — Plan and evaluate local AI media generation pipelines