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Neotex Knowledge Integration

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Use when working in projects with .neotex/ directory to retrieve organizational knowledge, search for patterns/guidelines/decisions, store learnings, or manage reference assets like images and files.

SKILL.md

Full skill instructions

Neotex Knowledge Integration

Overview

Neotex is an agent-first knowledge system for storing and retrieving organizational knowledge and assets. This skill integrates Claude Code with neotex via CLI commands.

Conversation Start: Auto-Check

At conversation start, check if neotex is initialized:

ls .neotex/​index.json 2>/​dev/​null
  • If exists: Note available knowledge (scan summaries, don't fetch all)
  • If missing but .neotex/ exists: Suggest neotex pull
  • If no .neotex/​: Skip neotex workflow unless user wants to initialize

When to Search

Search neotex when user asks about:

  • Organizational conventions, standards, guidelines
  • "How we do X here" or past decisions
  • Patterns or templates for common tasks
  • Reference images, mockups, or design files
neotex search "<query>" --limit 5
neotex search "type:guideline status:active path:backend <query>" --mode hybrid
neotex search "<query>" --source asset --mode lexical
neotex search "<query>" --exact
neotex get <id> --search-id <search_id>   # fetch if score > 0.7
neotex asset get <asset_id> --search-id <search_id>
  • Use --mode lexical for exact terms, filenames, or code identifiers
  • Use --exact to disable query expansion
  • Pass --search-id to help the system learn which results were selected

Precise Content Retrieval (VFS)

For large documents or when you need specific sections:

# Open with line range (like head/​tail)
neotex context open <id> --lines 0:100 --max-chars 4000

# Open specific chunk from search result
neotex context open <id> --chunk <chunk_id>

# List items matching filters (like ls)
neotex context list --path /​docs --type guideline --source knowledge
  • Search results include chunk_id for precise retrieval
  • Use --max-chars to limit response size (default 4000)
  • Prefer chunk retrieval over full document when search provides chunk_id

When to Store Knowledge

After completing significant work, evaluate:

  • Non-obvious solution others would benefit from?
  • Decision with tradeoffs worth documenting?
  • Reusable pattern or template?

If yes, ask user before storing:

"This involved [description]. Save to neotex as [type]: [title]?"

echo '{"type":"learning","title":"...","body_md":"# Title\n\n## Context\n..."}' | neotex add

When to Store Assets

IMPORTANT: When users upload reference files, proactively offer to save them to neotex.

Save assets when user provides:

  • Reference images (mockups, screenshots, diagrams)
  • Design files (logos, icons, UI specs)
  • Documentation PDFs
  • Configuration files for reference
  • Any file they want the team/​AI to access later

Prompt user:

"You uploaded [filename]. Save to neotex for future reference? I can add keywords and description for searchability."

# Upload an asset
neotex asset add <filepath> --description "..." --keywords "ui,mockup,login"

# Retrieve an asset
neotex asset get <asset_id> -o <output_path>

Asset Best Practices

  1. Always ask before saving - User may not want file persisted
  2. Add descriptive keywords - Makes assets searchable (e.g., "login, mockup, mobile, v2")
  3. Include context in description - Why this file matters, what it shows
  4. Link to knowledge when relevant - Associate asset with related documentation
  5. Retrieve before recreating - Search for existing assets before generating new ones

Knowledge Types

TypeUse For
guidelineRules to follow
learningInsights from experience
decisionArchitectural choices
templateReusable structures
checklistVerification steps
snippetReusable code

Common Mistakes

  • Fetching everything upfront: Search on-demand, not at start
  • Storing trivial changes: Only lasting organizational value
  • Duplicating: Search before creating
  • Storing secrets: Never include credentials or sensitive files
  • Ignoring uploaded files: Always offer to save reference materials
  • Missing keywords: Assets without keywords are hard to find later