Construct-AI-primary Knowledge Retrieval
Overview
This skill defines how to find and use existing knowledge before starting work. The enterprise has accumulated knowledge across many sessions and agents - this skill ensures you find and use it instead of rediscovering solutions. Always run this skill as the first step in any non-trivial task.
When to Use
- Before starting any new task or project
- When encountering a problem that seems familiar
- When asked to solve something another agent may have tackled
- When working in a domain outside your primary expertise
- Don't use when: Task is trivial, routine, or clearly has no prior knowledge available
Core Procedures
Step 1: Define the Search
Before searching, clarify what you're looking for:
- Topic: What domain or subject area?
- Problem type: What kind of problem (bug, design, process, analysis)?
- Keywords: What terms would relevant knowledge be tagged with?
- Scope: Which company, team, or system might have relevant knowledge?
Step 2: Search Strategy (in order)
Level 1: Direct Knowledge Check (always do)
- Check your own PARA resources and knowledge base
- Check relevant skill files for procedures
- Look for similar completed tasks in your history
Level 2: Cross-Agent Check (for non-trivial work)
- Search Gigabrain for tagged insights matching your keywords
- Check OpenStinger for cross-session patterns
- Look for relevant daily memory files from other agents
Level 3: Cross-Company Check (for novel or complex work)
- Check other companies' knowledge bases in same domain
- Search discipline-specific PARA entries across all companies
- Look for cross-company collaboration records
Step 3: Evaluate Retrieved Knowledge
For each piece of knowledge found:
- Relevance: Does this actually apply to my current problem?
- Currency: Is this still valid, or has something changed?
- Authority: Was this from a reliable source (tested, validated, expert agent)?
- Completeness: Is this the full solution or just a partial insight?
Step 4: Apply and Adapt
- Use retrieved knowledge as starting point, not final answer
- Adapt solutions to current context (don't copy blindly)
- Note any gaps between retrieved knowledge and current needs
- Document modifications for future knowledge capture
Step 5: Document the Search
If you searched and found nothing:
- Record that a search was performed and returned empty
- This is itself valuable knowledge (prevents redundant future searches)
- Capture any near-misses (similar but not quite applicable)
Quality Checklist
- Search was performed at appropriate depth for task complexity
- Retrieved knowledge was evaluated for relevance and currency
- Applied knowledge was adapted to current context
- Search results (including "nothing found") are documented
- Any knowledge gaps identified for future capture
Error Handling
- Error: Found knowledge but it's contradictory Response: Use most recent/authoritative source, flag contradiction for resolution
- Error: Found partial knowledge that doesn't fully solve the problem Response: Use what's available, fill gaps with best judgment, capture complete solution when done
- Error: Found outdated knowledge that no longer applies Response: Note the obsolescence, update or archive the old entry with current knowledge
- Error: Search returns overwhelming number of results Response: Narrow search scope, focus on most relevant tags, escalate to knowledge manager if pattern persists
Cross-Team Integration
Related Skills: knowledge-capture, taxonomy-standards, source-verification, lessons-learned-synthesis Used By: ALL agents as first step in non-trivial work