knowledge-management

name	knowledge-management
description	Universal knowledge storage and retrieval patterns using memory graph
license	MIT
compatibility	opencode
metadata	{"related_issue_tracking":"For tracking knowledge-related tasks, use skill `issue-tracking`","related_mcp_servers":"For MCP server integration, use skill `mcp-servers`"}

Knowledge Management

What I Do

Provide universal patterns for storing, retrieving, and managing project knowledge across different contexts and projects.

Universal Knowledge Management Patterns

Memory Storage Triggers

Store memories on these universal events:

• Solution implementation → Problem + solution + context
• Bug fix → Root cause + fix + prevention
• Architecture decision → Options + choice + rationale
• Pattern discovery → Reusable approach + examples

Memory Structure

# Universal memory fields
memory:
  type: solution | problem | code_pattern | fix | error | workflow
  title: "Specific, searchable title (not generic)"
  content: "Detailed explanation with context"
  tags: ["project-agnostic", "universal", "pattern"]
  importance: 0.8  # 0.8+ critical, 0.5-0.7 standard, 0.3-0.4 minor
  relationships: ["SOLVES:problem-1", "RELATED_TO:pattern-5"]

Universal Recall Patterns

# Universal knowledge recall
from memorygraph import recall_memories, search_memories

# Fuzzy recall for conceptual queries
results = recall_memories(
    query="timeout handling patterns",
    memory_types=["solution", "pattern"]
)

# Exact search for specific terms
exact_results = search_memories(
    tags=["timeout", "pattern"],
    min_importance=0.7
)

When to Use Me

Use this skill when:

• Implementing cross-project knowledge sharing
• Creating reusable solution patterns
• Standardizing documentation practices
• Building organizational memory systems

Universal Integration Examples

Cross-Project Knowledge Sharing

# Universal knowledge storage
store_memory(
    type="code_pattern",
    title="Universal timeout handling pattern",
    content="""
    def with_timeout(func, timeout=5, default=None):
        try:
            return func()
        except TimeoutError:
            return default
    """,
    tags=["python", "timeout", "pattern", "universal"],
    importance=0.9
)

Solution Relationships

# Universal relationship mapping
create_relationship(
    from_memory_id="solution-timeout-pattern",
    to_memory_id="problem-slow-api",
    relationship_type="SOLVES",
    context="Pattern addresses API timeout issues"
)

Best Practices

1. Tagging: Use consistent tags across projects for discoverability
2. Importance: Standardize importance scoring system
3. Relationships: Link related knowledge across projects
4. Maintenance: Regular knowledge base cleanup and organization

Compatibility

Designed for:

• Cross-project knowledge management
• Organizational learning systems
• Reusable pattern libraries
• Universal documentation standards