personal-ontologyHelp users build and maintain a Personal Ontology - a Palantir-style graph of Objects (identity, beliefs, predictions, goals) and Links (relationships between them) that enables AI-driven decision-making and life alignment.
Install via ClawdBot CLI:
clawdbot install levineam/personal-ontologyGrade Fair — based on market validation, documentation quality, package completeness, maintenance status, and authenticity signals.
Potentially destructive shell commands in tool definitions
exec(Audited Apr 17, 2026 · audit v1.0
Generated May 6, 2026
A user evaluates a job offer by cross-referencing it with their Core Self (Mission, Values), Goals, and active Projects. The agent surfaces alignment or conflict, enabling a decision grounded in personal ontology.
An AI agent generates a personalized morning briefing that restates the user's Mission, top Goal, and active Project, then suggests a concrete next output. This integrates ontology into daily workflow.
The agent scans the ontology for contradictory Links (e.g., a new Belief that contradicts an existing Prediction) and flags it for user review, ensuring consistency.
Based on Goals and Core Self, the agent proposes new Projects (e.g., a newsletter to serve a Goal about thought leadership) and presents them for user confirmation, avoiding orphan work.
The agent prompts the user to reflect on what served their Mission and Goals that day, capturing insights and adjusting the ontology incrementally.
Provide the ontology framework as a SaaS product with tiered subscriptions (individual, team). Revenue from monthly/yearly fees.
Offer the ontology as a tool for life coaches and therapists, who subscribe to use it with clients. Revenue per coach + per active client.
License the ontology system to HR departments for employee career development, integrating with existing goal-setting platforms.
💬 Integration Tip
Start by embedding the ontology into a daily routine app like a morning briefing or task manager, using the live ontology files as a data source.
Scored May 6, 2026
Search and analyze your own session logs (older/parent conversations) using jq.
Typed knowledge graph for structured agent memory and composable skills. Use when creating/querying entities (Person, Project, Task, Event, Document), linkin...
Audit, clean, and optimize Clawdbot's vector memory (LanceDB). Use when memory is bloated with junk, token usage is high from irrelevant auto-recalls, or setting up memory maintenance automation.
Enable and configure Moltbot/Clawdbot memory search for persistent context. Use when setting up memory, fixing "goldfish brain," or helping users configure memorySearch in their config. Covers MEMORY.md, daily logs, and vector search setup.
Local memory management for agents. Compression detection, auto-snapshots, and semantic search. Use when agents need to detect compression risk before memory loss, save context snapshots, search historical memories, or track memory usage patterns. Never lose context again.
You MUST use this for gathering contexts before any work. This is a Knowledge management for AI agents. Use `brv` to store and retrieve project patterns, dec...