Manages a knowledge graph taxonomy for the StakTrakr project using Neo4j.
npx skills add https://github.com/lbruton/StakTrakr --skill memento-taxonomy
Please help me install this Agent Skill. Skill: memento-taxonomy Source: https://github.com/lbruton/StakTrakr/tree/main/.claude/skills/memento-taxonomy Command: npx skills add https://github.com/lbruton/StakTrakr --skill memento-taxonomy
This Skill provides a standardized taxonomy, naming conventions, and search patterns for managing a knowledge graph, ensuring consistency and efficient retrieval of information within the StakTrakr project.
Type: PROJECT-THEME-YYYYMMDD-HHMMSS pattern for entities like Handoffs, Sessions, and Insights.STAKTRAKR:DEVELOPMENT:HANDOFF, STAKTRAKR:FRONTEND:INSIGHT).Use the memento-taxonomy skill to create a new handoff entity with the following details.
High-intent search queries and answers about installing and using this skill.
Entity naming conventions for a Neo4j knowledge graph use a standardized Type: PROJECT-THEME-YYYYMMDD-HHMMSS pattern to ensure consistent data organization and retrieval. This structure applies to entities like Handoffs, Sessions, and Insights.
You search for development handoffs and insights using optimized query patterns like search_nodes and semantic_search functions. These patterns retrieve specific entities by topic, version, or project while enforcing required tags and observations.
Managing development sessions and handoffs requires a taxonomy defining specific entity types like STAKTRAKR:DEVELOPMENT:HANDOFF and STAKTRAKR:FRONTEND:INSIGHT. It mandates essential observations and tags to ensure project isolation and data completeness.
Yes, you can isolate knowledge graph data by active Linear project. The taxonomy mandates specific tags for every entity to ensure strict project isolation and prevent data overlap across different development streams.
Logging a development session requires metadata including the active Linear project, next steps, required observations, and specific tags. This ensures seamless continuation of work and complete retrieval of session history.
Semantic search works with tagged knowledge graph entities by utilizing defined safety rules and entity structures within Neo4j graph storage. It leverages standardized naming and mandated tags to retrieve matching sessions and insights efficiently.
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