broomva

revenuecast — turn a real-world capability into a self-demonstrating, high-throughput generative-AI revenue engine (the "Kleos" method). It is "/skillify for revenue": skillify turns a workflow into a tested skill; revenuecast turns a capability into a revenue engine whose own output IS the advertisement. The bstack-native composition of the 2026 "show-then-sell-the-system" creator loop (realosias, aivideoskool, GenHQ): Brand-Lock -> Show -> Distribute -> Hook -> Sell -> Moat, where the showcased output's desirability + accessibility-via-AI creates demand for the method, and you monetize the reproducible system. Composes content-engine (the factory), content-creation, blog-post, seo-llmeo, arcan-glass, social-intelligence, strategy-skills, and symphony/arcan (autonomous runtime). Its deterministic core (scripts/revenuecast_check.py) gates an engine-instance manifest on the design canon — own-the-audience, a real moat (not leakable prompts), the compliance/survival pillar (FTC v. Air AI / EU AI Act Art.50 / NO

Skillify-as-a-verb — distill a working session (or a pointed-at chat history) into a permanent, TESTED, registered skill at the end of a workflow. The bstack-native composition of Garry Tan's 10-step "skillify it": look-back extraction → CreateSkill scaffold → latent/deterministic split → unit tests → resolver-eval (role-x.py eval) → script-test gate (bstack skills audit --require-tests) → P20 cross-review → bookkeeping file. Composes existing primitives; reimplements nothing. The deterministic core (scripts/skillify_check.py) makes "a feature that doesn't pass all ten is not a skill" machine-checkable. USE WHEN: "skillify it", "skillify this", "package this as a skill", "distill this into a skill", "make this a skill", "turn this into a skill", or at the end of an ad-hoc workflow that worked and should become permanent. NOT FOR: ingesting an external artifact (use /checkit); retrospective "what have I done repeatedly" discovery alone (use the look-back lens); a one-off task with no reusable procedure.

Fresh-session handoff doc drafting. Produces a stable, single-file human-readable narrative state for the NEXT agent context (fresh session, after `/clear`, after persist iteration, after a tab close). The artifact lives at `docs/handoffs/YYYY-MM-DD-<arc>.md` and follows a stable shape: TL;DR + State-of-the-world (P15 snapshot) + What-was-delivered (PR table with SHAs) + First action + Pickup state. Distinct from P12 persist's `PROMPT.md` (machine-state for cross-context loop) and the P1 Bridge session log (raw transcript) — the handoff is the narrative bridge a human reads in ten seconds and a fresh agent reads in thirty. Use when: (1) ending a substantive session that another agent will continue, (2) preparing a fresh-session pickup point mid-arc, (3) needing to compress a multi-PR arc into a single resumable document, (4) the user says "write a handoff" / "fresh-session handoff" / "let me come back to this tomorrow". Triggers on "handoff", "fresh-session", "fresh session", "pickup", "where we are", "leave

Investment management skill — portfolio construction, analysis, and execution. Compounds finance-substrate (accounting/tax) + wealth-management (projections/goals) into a full financial framework. Covers traditional investing (stocks, ETFs, bonds), alternatives (crypto, prediction markets, real estate, VC), quantitative analytics (factor models, Monte Carlo, optimization), and platform integration (Alpaca, Coinbase, Polymarket, agent-browser for Colombian platforms). Embodies philosophies from Buffett, Dalio, Bogle, Munger, and Marks. Use when: (1) building or analyzing a portfolio, (2) screening stocks/ETFs/crypto, (3) running backtests or factor analysis, (4) executing trades or rebalancing, (5) tracking investments across platforms, (6) researching market data or fundamentals, (7) making investment decisions with structured frameworks. Triggers on 'investment', 'portfolio', 'stocks', 'ETF', 'bonds', 'crypto', 'trading', 'backtest', 'factor model', 'rebalance', 'Polymarket', 'Alpaca', 'asset allocation'.

Estimate optimal waiting time for Alkosto's "every 25/50 customers" promotion using either checkout-flow observations or winner announcement timestamps. Use when the user asks how long to wait, wants a probability-based cutoff, or needs a fast in-store decision rule with uncertainty handling.

Agentic robotics with CaP-X — LLM-driven robot manipulation via code generation. Use when: (1) Setting up CaP-X / CaP-Gym environments for robot manipulation benchmarks, (2) Running CaP-Bench evaluations across LLMs/VLMs on robotic tasks, (3) Building or extending CaP-Agent0 agentic harnesses (skill libraries, visual differencing, parallel reasoning), (4) Training robot coding agents with CaP-RL (GRPO on code generation), (5) Developing perception APIs (SAM3, Molmo, depth, point clouds) or control APIs (IK solvers, grasp planners), (6) Sim-to-real transfer for Franka Panda, R1Pro humanoid, or other robot platforms, (7) Designing auto-synthesized skill libraries for physical manipulation (Voyager-style), (8) Integrating agentic robotics with Life Agent OS (Arcan orchestration, Spaces agent networking, Lago persistence), (9) Any task involving LLM-based robot control, manipulation benchmarks, robotic code synthesis, or embodied AI agents.

Implement OpenAI Harness Engineering practices in any repository — AGENTS.md, PLANS.md, deterministic smoke/test/lint harness commands, strict architecture boundaries, observability from day 1, and entropy-control audits for reliable autonomous agent runs.

Local TTS, voice cloning, voice design, and video dubbing via the OmniVoice Studio MCP server (open-source ElevenLabs alternative; nothing leaves the machine, runs on MPS/CUDA/CPU). Use when: (1) generating speech from text in any of 646 languages, (2) cloning a voice from a 3-second reference clip, (3) designing a voice by gender/age/accent/pitch/style, (4) dubbing a video into another language, (5) listing voice profiles or personality presets, (6) producing narration where privacy, cost, or absent API keys matter, (7) non-English narration where Edge TTS/kokoro fall short, (8) batch audio for blog posts or content pipelines. Triggers: 'omnivoice', 'voice clone', 'clone this voice', 'tts', 'narrate', 'generate speech', 'voice synthesis', 'dub video', 'voice design', 'local tts', 'multilingual voice', 'narrate this post', 'elevenlabs alternative'.

Strategy & Decision Intelligence — 8 skills for personal productivity, strategic thinking, and decision-making. Pre-mortem risk analysis, braindump capture to Obsidian vault, morning briefings, priority drift detection, strategy red-teaming, multi-audience stakeholder updates, structured decision logging, and weekly reviews. All skills integrate with the Obsidian vault and knowledge-graph-memory for persistent context. Use when: (1) planning or evaluating a project, (2) capturing thoughts or decisions, (3) generating briefings or reviews, (4) checking strategic alignment, (5) user says "pre-mortem", "braindump", "morning briefing", "drift check", "strategy critique", "stakeholder update", "decision log", "weekly review".

Run a premortem on any plan, launch, product, hire, strategy, or decision. Assumes it already failed 6 months from now and works backward to find every reason why. Produces a revised plan with blind spots exposed. MANDATORY TRIGGERS: 'premortem this', 'premortem my', 'run a premortem', 'what could kill this', 'future-proof this', 'stress test this plan', 'what am i missing here', 'find the blind spots'. STRONG TRIGGERS: 'what could go wrong', 'am i missing anything', 'poke holes in this', 'where will this break', 'devil's advocate this'. Do NOT trigger on simple feedback requests, factual questions, or LLM Council requests. DO trigger when someone has a plan or commitment where the cost of being wrong is high.

Takes raw unstructured thoughts, voice transcript dumps, or stream-of-consciousness text and auto-files them into the right Obsidian vault folders with tags, backlinks, and proper frontmatter. Use when the user says "braindump", "brain dump", "capture this", "dump my thoughts", "I'm thinking about...", or provides a long unstructured block of text to organize.

Captures a decision with context, alternatives considered, and rationale, then links it to the relevant project doc in the vault. Creates a searchable decision record. Use when the user says "decision log", "log this decision", "record this choice", "document why we chose", "decision record", "ADR", or has just made an important decision.

Compares stated priorities against where time and effort actually went, and produces a strategy drift report. Uses git log, vault priorities, and project docs to detect misalignment. Use when the user says "drift check", "am I on track", "priority alignment", "where did my time go", "strategy drift", or wants to audit focus vs intention.

Reads open action items, this week's priorities, and recent vault updates, then produces a focused "start your day" brief. Use when the user says "morning briefing", "daily brief", "what's on my plate", "start my day", "what should I focus on today", or at the start of a work session.

Assumes a project has already failed, works backward to identify the top causes, scores them by likelihood and impact, and outputs a mitigation plan. Use when starting a new project, before a major launch, evaluating risky decisions, or when the user says "pre-mortem", "what could go wrong", "risk analysis", "failure modes", "red team this plan".

Takes one set of project facts and generates three versions: technical for engineering, business-impact for leadership, and customer-facing for success teams. Use when the user says "stakeholder update", "write an update", "communicate this to different audiences", "translate for leadership", "customer-facing version", or needs to communicate the same information to different audiences.

Agent-facing interface to the Lago knowledge substrate. Provides Karpathy-style wiki operations (ingest, search, read, write, lint, wake-up, query) on top of Lago's event-sourced, content-addressed filesystem.

Create and maintain a control-system metalayer for autonomous code-agent development in any repository. Use when you need explicit control primitives (setpoints, sensors, controller policy, actuators, feedback loop, stability and entropy controls), repo command/rule governance, and a scalable folder topology that lets agents operate safely and keep improving over time.

Build or modify aiOS control-plane HTTP/SSE behavior. Use when changing apps/aios-api routes, request/response models, streaming/replay semantics, approval endpoints, or API compatibility guarantees.

Evolve core aiOS kernel behavior and contracts. Use when modifying crates aios-model, aios-events, aios-policy, aios-tools, aios-memory, aios-runtime, or aios-kernel, especially for event schema, lifecycle phases, capability checks, checkpoints, memory provenance, or session semantics.

Prepare aiOS for production release and distribution. Use when hardening CI/CD, observability, security boundaries, packaging, deployment, rollback strategy, and operational readiness.

Detect unused dependencies in Rust projects for cleaner Cargo.toml files and faster builds. Use when auditing dependencies, optimizing build times, cleaning up Cargo.toml, or detecting bloat. Trigger terms: unused dependencies, cargo-machete, dependency audit, dependency cleanup, bloat detection, cargo-udeps.

Run full workspace validation (format, lint, build, test)

Pre-release verification for crates.io publishing

Reference for the `broomva` Rust CLI — manage prompts, skills, and context from the terminal or Claude Code sessions. Includes the auto-tracing protocol that turns this skill into the runtime dispatcher for broomva.tech/prompts. When a user asks to "use the X prompt", "run the X prompt as instructions", or "pull X prompt", this skill is the answer.

Skill: lazy-prefetch-pattern

Skill: react

Skill: trpc-patterns

Skill: typescript

Skill: ultracite

Umbrella skill package containing three complementary skills for persistent consciousness in autonomous AI agent development — control primitives and behavioral governance, agent consciousness architecture, and knowledge graph memory. Install individual skills or use the full stack to give stateless agent sessions the accumulated understanding of all prior sessions. Part of the Broomva Stack (Layers 1-2).

Persistent consciousness architecture for autonomous AI agent development. Synthesizes three substrates — control metalayer (behavioral governance), Obsidian knowledge graph (declarative memory), and conversation log bridge (episodic memory) — into a self-evolving context layer. Use when designing agent memory systems, implementing cross-session context persistence, building knowledge graphs for AI agents, setting up conversation history capture, or architecting feedback loops that let agents learn from prior sessions. Triggers on "agent memory", "session persistence", "knowledge graph", "conversation history", "consciousness stream", "cross-session context", "agent learning", or "self-evolving development".

Bridge Claude Code conversation logs to an Obsidian knowledge graph for persistent agent memory. Transforms .entire/ event logs and ~/.claude/ transcripts into searchable, wikilinked markdown docs with full conversation threads, tool call details, and session metadata. Use when setting up conversation history capture, configuring knowledge graph traversal for agents, building episodic memory from session logs, or connecting agent work to an Obsidian vault. Triggers on "conversation history", "session logs to obsidian", "knowledge graph memory", "agent episodic memory", "conversation bridge", "session documentation", or "knowledge traversal".

Create and maintain a control-system metalayer for autonomous code-agent development in any repository. Use when you need explicit control primitives (setpoints, sensors, controller policy, actuators, feedback loop, stability and entropy controls), repo command/rule governance, and a scalable folder topology that lets agents operate safely and keep improving over time.

AI feature development skill. Use when adding models, tools, providers, or streaming features to chatOS.

Deployment skill for chatOS. Use when deploying to Vercel, running DB migrations, or configuring environments.

Development workflow skill for the chatOS monorepo. Use when setting up, building, testing, or contributing to chatOS.

Implement OpenAI Harness Engineering practices in any repository — AGENTS.md, PLANS.md, deterministic smoke/test/lint harness commands, strict architecture boundaries, observability from day 1, and entropy-control audits for reliable autonomous agent runs.

Implement OpenAI Harness Engineering practices in any repository. Use when setting up or refactoring agent-first workflows, writing or upgrading AGENTS.md and PLANS.md, creating deterministic smoke/test/lint/typecheck harness commands, defining strict architecture boundaries and data-shape contracts, wiring observability from day 1, and adding entropy-control checks plus CI automation for reliable autonomous runs.

Rust orchestration engine for coding agents. Polls issue trackers (Linear, GitHub), creates isolated per-issue workspaces, and runs coding agent sessions with lifecycle hooks, retry/backoff, concurrency control, and a live HTTP dashboard. Includes control metalayer (CONTROL.md / setpoints) for grounded development workflows.

Expert guidance for Symphony — the Rust orchestration engine for coding agents. Use when users ask about installing Symphony (cargo install, curl|bash, docker), initializing projects (symphony init), configuring WORKFLOW.md for Linear or GitHub trackers, running in daemon or one-shot mode, setting up the control metalayer (CONTROL.md, setpoints), configuring lifecycle hooks (after_create, before_run, after_run, pr_feedback), monitoring with HTTP dashboard and Prometheus /metrics, extending with new trackers, or troubleshooting agent/hook failures. Triggers on "symphony", "WORKFLOW.md", "coding agent orchestration", "issue tracker automation", "control metalayer", or "agent dispatch".

Evaluator-Governed Recursive Improvement (EGRI) framework for turning ambiguous goals into safe, measurable, rollback-capable recursive improvement systems. Use when the user wants to: (1) build a self-improving system for any domain (ML, RAG, workflows, ETL, UI, compiler tuning, etc.), (2) formalize a vague optimization goal into a bounded loop with evaluator, harness, and promotion policy, (3) create an autoresearch-style system beyond ML training, (4) design a mutable-artifact + immutable-evaluator architecture, (5) scaffold a problem-spec for recursive improvement, (6) turn "make X better" into a safe, auditable optimization process. Triggers on: "self-improving", "autoresearch", "autoany", "EGRI", "recursive improvement", "optimization loop", "evaluator-governed", "harness + evaluator", "mutable artifact", "problem compiler", "benchmark loop", "mutation surface".

Evaluator-Governed Recursive Improvement (EGRI) framework for turning ambiguous goals into safe, measurable, rollback-capable recursive improvement systems. Use when the user wants to: (1) build a self-improving system for any domain (ML, RAG, workflows, ETL, UI, compiler tuning, etc.), (2) formalize a vague optimization goal into a bounded loop with evaluator, harness, and promotion policy, (3) create an autoresearch-style system beyond ML training, (4) design a mutable-artifact + immutable-evaluator architecture, (5) scaffold a problem-spec for recursive improvement, (6) turn "make X better" into a safe, auditable optimization process. Triggers on: "self-improving", "autoresearch", "autoany", "EGRI", "recursive improvement", "optimization loop", "evaluator-governed", "harness + evaluator", "mutable artifact", "problem compiler", "benchmark loop", "mutation surface".

bstack — the Broomva Stack. Twenty irreducible primitives (P1-P20) plus 30 curated skills that turn an agent-driven workspace into a self-operating system. Each primitive closes one specific failure mode (session amnesia, destructive ops, invisible work, dirty-tree drift, context rot, ritual phrases without substance, single-model echo chambers). The canonical operating mode is broomva/autonomous (fires every reflex without prompting). Use when: (1) bootstrapping a new agent-driven workspace, (2) verifying primitive compliance via 'bstack doctor', (3) repairing missing governance/hooks/policy via 'bstack repair', (4) listing installed-vs-missing skills via 'bstack status', (5) validating skill frontmatter health via 'bstack validate', (6) full reconfiguration via 'bstack revamp'. Triggers on 'bstack', 'broomva stack', 'bootstrap project', 'install all skills', 'P1' through 'P20', 'agent harness', 'self-operating workspace'.

Upgrade bstack to the latest version. Detects global vs vendored install, runs the upgrade, and shows what's new.

BroomVA trademark web styling system with glass/frosted effects, dark-first themes, and AI Blue tokens for Next.js + Tailwind v4 + shadcn/ui. Provides a drop-in globals.css, glass component patterns (card, nav, button, modal, sidebar, badge), OKLCh color system with P3 gamut enhancement, and composable animation presets. Use when creating or styling BroomVA web interfaces, implementing frosted glass UI effects, setting up brand-consistent dark-first themes, or integrating ArcanBG brand tokens (AI Blue #0066FF, Web3 Green #00CC66).

BroomVA trademark web styling system — Arcan Glass design language for Next.js + Tailwind v4 + shadcn/ui projects. Use when creating or styling BroomVA web interfaces, implementing glass/frosted UI effects, setting up brand-consistent dark-first themes, or integrating ArcanBG brand tokens (AI Blue

Set up, configure, and run LTX-2/LTX-2.3 (Lightricks) for AI video and audio generation. Use when: (1) Installing LTX-2 locally or via ComfyUI, (2) Generating video from text, image, audio, or keyframes, (3) Running inference with the 22B dev/distilled models, (4) Fine-tuning with LoRA/IC-LoRA, (5) Configuring upscalers (spatial/temporal), (6) Optimizing VRAM usage (FP8, quantization, low-VRAM modes), (7) Building content-generation pipelines with LTX-2, (8) Writing prompts for video generation, (9) Integrating LTX-2 into ComfyUI workflows. Triggers on: ltx, ltx-video, ltx-2, lightricks video, text-to-video generation, video diffusion model.