Wiki Ingest
Ingest articles, PDFs, videos, transcripts, and notes into a persistent interlinked knowledge wiki and V6 knowledge operating system. Use when the user wants source notes, entity pages, concept pages, navigation updates, STOW processing, Obsidian provenance, clipping lifecycle handling, or supervised promotion of source-derived insights into skills, SOPs, schemas, daily loops, or governance queue…
Startup Evaluation
Evaluate startup health using entrepreneurship, VC, and execution frameworks. Use when assessing a startup idea, company, pitch, due diligence target, fundraising readiness, or business model health.
Ai Six Sigma Property Os
Design an AI Six Sigma Black Belt operating model for property service, maintenance dispatch, environmental testing, quote generation, CRM follow-up, and workflow quality dashboards. Use when the user needs a Property Agent OS, AI + Ontology + DMAIC management system, CTQ metrics, agent-team roles, work-order states, or MVP roadmap for operations quality.
Deep Research
Multi-source deep research — search, synthesize, and deliver cited reports. Use when the user wants thorough research on any topic with evidence and citations.
Agentic Engineering
Design or refactor agent skills, workflows, operating loops, and V6 knowledge-OS upgrades for model-native Agentic Engineering. Use when making skills more autonomous, concise, verifiable, long-horizon capable, token-efficient, lower-friction for human-LLM collaboration, or ready to promote Obsidian wiki learning into reusable agent behavior.
Session Learn
Extract reusable knowledge from a work session and save concepts, entities, corrections, patterns, ideas, decisions, and gaps to the wiki. Use when ending a session or when the user says to extract knowledge.
Context Manager
Manage the LLM's context window — token budgeting, prompt assembly, truncation strategies. Use when approaching context limits or optimizing prompt costs.
Creativity Engine
Generate, validate, and output new ideas based on existing knowledge. Combines combinatorial creativity, cross-domain analogy, and minimum experiments. Use when the user wants fresh ideas, new product concepts, or creative solutions.
Behavior Design
Design a behavior change system — decompose a goal into minimum habits, define triggers, build SOPs, and set up review cycles. Use when the user wants to build a habit, change behavior, or achieve a personal goal.
Cognitive Compile
Deep learning compile framework — transforms raw information into actionable judgment. Use when the user wants to deeply understand a topic, not just capture it.
Daily Okr
Execute a V6 daily knowledge compound closed loop — 7 Key Results from input to feedback with scoring, evidence, wiki write-back, and optional scheduled Obsidian daily-loop note. Use when the user wants to do a daily review, plan their day, run a knowledge workflow, or complete the generated daily knowledge-management loop.
Harness Engineering
Design V6 runtime infrastructure around AI agents — permissions, tools, MCP/Skills/Hooks, feedback loops, observability, scheduled routines, and governance. Use when deploying agents to production, designing multi-agent systems, building agent harnesses, or turning Obsidian wiki rules into bounded runtime controls.
Agent Teams Command
Command V6 multi-agent work with bounded roles, ownership, worktree isolation, IPC, integration gates, cleanup, attention budgets, and verification loops. Use when the user needs Claude Code Agent Teams, parallel agents, delegation strategy, Ender-style commander training, Palantir-style ontology command boards, FDE field discovery, EDD integration gates, dynamic workflow tradeoffs, or multi-agen…
Knowledge Ops
Manage a multi-layered V6 knowledge operating system — organize, deduplicate, retrieve, lint, queue, sync, and operate wiki files, vector DB, memory, daily loops, Agent/Wiki flywheel reports, and external stores. Use when the user wants to save, organize, search, scale, audit, or turn Obsidian wiki knowledge into supervised skill/SOP/schema improvement candidates.
Wiki Lint
Health-check the V6 knowledge wiki — find orphans, broken links, missing frontmatter, contradictions, stale content, statistical drift, source/provenance debt, daily-loop health, and rule-promotion readiness. Use when the user says "lint the wiki", "health check", "check Obsidian system", "verify the knowledge loop", or periodically for maintenance.
Loop Engineering
Turn a repeatable task into a bounded, evidence-driven agent loop. Use when Codex needs to decide whether a task merits a Goal, Loop, Automation, or AutoResearch pattern; define a loop contract; check trigger/state/tools/codebase readiness; choose single-agent versus maker-checker versus manager-workers topology; prevent runaway iteration; or repair a loop that stalls, self-grades, exceeds review…
Anthropic Os
Improve a personal or team operating system with self-evolving loops, CASH allocation, 3B creativity, predictive coding, and diagnostics. Use when the user wants to redesign a work method, learning loop, or cognitive operating system.
Verify Before Claim
Iron rule — no completion claims without fresh verification evidence. Use whenever about to claim work is done, fixed, working, or passing. Run verification commands and show output before making any success statement.
Project Flow Ops
Operate execution flow — triage tasks, manage priorities, keep progress structured. Use when the user needs backlog control, task planning, or workflow coordination across projects.
Ai Six Sigma Property Os
Use when property-service operations need an AI plus ontology plus DMAIC design for work orders, dispatch, quotes, evidence, CTQ metrics, and control dashboards.
Wiki Lint
Use when an Obsidian wiki needs a reproducible health audit for structure, provenance, links, understanding, lifecycle, and promotion readiness.
Cognitive Compile
Use when source material must be transformed into a compact, evidence-aware model for learning, decisions, or an Obsidian concept note.
Session Learn
Use when a completed work session should yield durable concepts, corrections, decisions, reusable patterns, and a traceable next action.
Verify Before Claim
Use when an agent is about to claim completion, correctness, safety, publication, deployment, or any consequential external fact.
Harness Engineering
Use when an agent workflow needs production-like runtime controls for context, tools, permissions, observability, scheduling, evaluation, recovery, or maintenance.
Behavior Design
Use when a goal must be converted into a repeatable behavior, cue, SOP, review cadence, and identity-aligned reinforcement.
Anthropic Os
Use when a personal or team operating system needs a bounded redesign using Four-C, closed-loop controls, 70/30 allocation, 3B creativity, experiments, and prediction-error learning.
Context Manager
Use when a long-running agent task needs context budgeting, checkpointing, compaction, retrieval, or capability-based model routing.
Knowledge Ops
Use when an Obsidian knowledge system needs classification, deduplication, retrieval, synchronization, debt queues, or governed Agent/Wiki promotion.
Loop Engineering
Use when a repeatable task must become a bounded Trigger -> Execute -> Verify -> State loop, scheduled automation, goal agent, or metric-driven research cycle.
Wiki Ingest
Use when a PDF, URL, transcript, clipping, or raw note must become source-grounded, linked, governed knowledge in an Obsidian vault.
Project Flow Ops
Use when projects or tasks need explicit state, WIP control, ownership, definitions of done, blocker handling, and verified closure.
Agent Teams Command
Use when work has genuinely independent streams or distinct builder, evaluator, domain, and integration roles that require bounded multi-agent command.
Daily Okr
Use when planning or closing a daily knowledge-compounding cycle across input, cognition, wiki, behavior, creativity, output, and feedback.
Deep Research
Use when a decision-relevant question needs multi-source search, claim-level citations, contradiction handling, uncertainty, or a durable wiki handoff.
Creativity Engine
Use when a defined problem needs diverse ideas, cross-domain combinations, and cheap experiments instead of a single untested answer.
Agentic Engineering
Use when designing or refactoring a model-native engineering workflow with bounded autonomy, probes, custom evaluation, durable state, and verified write-back.
Graph Engineering
Use when a workflow has explicit data dependencies, independently executable branches, typed joins, or node-local recovery needs that justify a bounded static dependency graph.
Startup Evaluation
Use when a startup needs an evidence-weighted health check, investor lens, runway diagnosis, top constraint, or cheapest next validation test.