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:

1. Relevance: Does this actually apply to my current problem?
2. Currency: Is this still valid, or has something changed?
3. Authority: Was this from a reliable source (tested, validated, expert agent)?
4. 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