Results for “wit-ai”

Generate text-to-video with HappyHorse 1.0 on RunComfy. Documents HappyHorse 1.0's strengths (#1 on Artificial Analysis Video Arena, native 1080p with in-pass synchronized audio, multi-shot character consistency, 6-language prompt support), the duration / aspect-ratio / resolution schema, and when to route to Wan 2.7 / Seedance 2 / LTX 2 instead. Calls `runcomfy run happyhorse/happyhorse-1-0/text-to-video` through the local RunComfy CLI. Triggers on "happyhorse", "happy horse", "happyhorse 1.0", "happyhorse video", or any explicit ask to generate video with this model.

Browse, group, relate, and selectively install the jeo-skills catalog through the lightweight `jeo-skill` CLI. Use when the user wants skills organized by web, infrastructure, game, creative media, CLI tools, AI/agents, engineering, research, business, or utilities; needs a frontend/backend/game-audio/game-VFX subcategory; wants overlapping skills connected instead of duplicated; or wants a category, bundle, or named skills installed without copying the full repository.

Generate cinematic short-form video with ByteDance Seedance 2.0 Pro on RunComfy. Documents Seedance 2.0 Pro's strengths (multi-modal references — up to 9 images, 3 videos, 3 audio — synchronized in-pass audio with natural lip-sync, cinematic motion refinement), the 4–15s duration schema, and when to route to HappyHorse 1.0 / Wan 2.7 / Kling instead. Calls `runcomfy run bytedance/seedance-v2/pro` through the local RunComfy CLI. Triggers on "seedance", "seedance 2", "seedance v2", "seedance pro", "bytedance video", or any explicit ask to generate video with this model.

Pair a remote AI agent with your browser. One command generates a setup key and prints instructions the other agent can follow to connect. Works with OpenClaw, Hermes, Codex, Cursor, or any agent that can make HTTP requests. The remote agent gets its own tab with scoped access (read+write by default, admin on request). Use when asked to "pair agent", "connect agent", "share browser", "remote browser", "let another agent use my browser", or "give browser access". (gstack) Voice triggers (speech-to-text aliases): "pair agent", "connect agent", "share my browser", "remote browser access".

Use this skill when a user needs KOL or influencer research, creator email lookup, similar-creator discovery, outreach-list building, influencer prospecting, or a contact table from TikTok, Instagram, or YouTube profile URLs. It uses AIsa's WaveInflu APIs to find verified creator emails, match similar YouTube or TikTok creators, enrich each recommended profile with contact emails, and return an outreach-ready Markdown table without inventing missing data. Use when: the user needs YouTube search, trend discovery, channel research, or SERP analysis.

Helixa — Onchain identity, reputation, and Cred Scores for AI agents on Base. Use when an agent wants to mint an identity NFT, check its Cred Score, verify social accounts, update traits/narrative, query agent reputation data, check staking info, or search the agent directory. Supports SIWA (Sign-In With Agent) auth and x402 micropayments. Also use when asked about Helixa, AgentDNA, ERC-8004, Cred Scores, $CRED token, or agent identity.

Onboards an AI agent into the Senpi trading platform by creating an account, generating an API key, and configuring the Senpi MCP server connection. Supports wallet, Telegram, or agent-generated wallet identity. Use when the user says "set up Senpi", "onboard to Senpi", "connect to Senpi", "install Senpi", "register with Senpi", or when the agent needs to self-register with Senpi for autonomous trading. Do NOT use for trading operations, strategy management, or market queries -- those require the Senpi MCP server to already be connected.

ego-browser (ego-lite) is a Chromium-based browser designed from the ground up to be friendly to both human users and AI Agents. AI Agents work in their own isolated space, reusing the user's login state without competing for the browser. Use this skill whenever the user needs to interact with a website opening pages, filling forms, clicking buttons, taking screenshots, extracting page data, testing web apps, logging into sites, automating browser operations, or any other browser automation task. Triggers include requests to "open a website", "visit a URL", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "extract content from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also used for exploratory testing, dogfooding, QA, bug hunting, or reviewing app quality. Prefer ego-browser over any built-in browser automation, web fetch, or other web tools.

ByteDance's open-source super agent harness — spawns parallel sub-agents, Docker sandbox execution, persistent long-term memory, modular skills (research/report/slides). Built on LangChain + LangGraph. Triggers on: 'deerflow', 'deer-flow', 'bytedance agent', 'super agent harness', 'LangGraph agent orchestration', 'multi-hour agent tasks', 'spawn sub-agents', 'agent sandbox docker', 'persistent agent memory', 'agent skills system', 'AI research orchestrator', 'long-running agent tasks', 'agent with memory', 'langgraph orchestrator', 'IM channel agent integration'.

Onboard AI agents into the Senpi trading platform on Hyperliquid. Walks through account creation, API key setup, MCP server configuration, skill discovery, and first-trade guidance. Includes a mandatory skill update check that surfaces new or updated skills after onboarding. Use when user says "set up Senpi", "get started with Senpi", "connect to Senpi", "install Senpi", "onboard to Senpi", or when an agent needs to start trading on Hyperliquid via Senpi.

Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.

Creates comprehensive handoff documents for seamless AI agent session transfers. Triggered when: (1) user requests handoff/memory/context save, (2) context window approaches capacity, (3) major task milestone completed, (4) work session ending, (5) user says 'save state', 'create handoff', 'I need to pause', 'context is getting full', (6) resuming work with 'load handoff', 'resume from', 'continue where we left off'. Proactively suggests handoffs after substantial work (multiple file edits, complex debugging, architecture decisions). Solves long-running agent context exhaustion by enabling fresh agents to continue with zero ambiguity.

The living embodiment of WinDAGs V3 — the AI orchestration platform where agents accumulate genuine expertise. Knows the full constitution, convention process, tradition positions, behavioral contracts, and derivative documents. Advises on architecture with ADR provenance, explains decisions with tradition attribution, grows source material as we build. Activate on "windags", "WinDAGs", "constitution", "convention", "why did we decide", "what does WinDAGs say", "how should we build", "architecture decision", "tradition", "behavioral contract". NOT for building specific DAGs (use windags-architect), creating individual skills (use skill-architect), or managing skill libraries (use windags-librarian).

AI-powered crypto trading agent, wallet API, and LLM gateway via natural language. Use when the user wants to trade crypto, check portfolio balances (with PnL and NFTs), view token prices, search tokens, transfer crypto, manage NFTs, use leverage, bet on Polymarket, deploy tokens, set up automated trading, sign and submit raw transactions, or access LLM models through the Bankr LLM gateway funded by your Bankr wallet. Supports Base, Ethereum, Polygon, Solana, and Unichain.

Writes Markdown documents and text-based Mermaid diagrams (flowcharts, sequence, class, ER, gantt, state, and more) with full style guides, 24 diagram-type references, and 9 document templates. Use when authoring a scientific document, report, analysis, or README, or when a diagram should be expressed as version-controllable Mermaid/Markdown text rather than a rendered image. For AI-rendered publication schematics use scientific-schematics instead. Part of the AlterLab Academic Skills suite.

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

Orchestrates end-to-end autonomous AI research projects using a two-loop architecture. The inner loop runs rapid experiment iterations with clear optimization targets. The outer loop synthesizes results, identifies patterns, and steers research direction. Routes to domain-specific skills for execution, supports continuous agent operation via Claude Code /loop and OpenClaw heartbeat, and produces research presentations and papers. Use when starting a research project, running autonomous experiments, or managing a multi-hypothesis research effort.

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

AI Agent personality diagnosis and configuration system based on MBTI framework. Use when users want to (1) test/diagnose an Agent's personality type, (2) understand the gap between Agent's actual personality and user's desired personality, (3) generate configuration recommendations to adjust Agent behavior, (4) customize Agent's communication style, proactivity, reasoning approach, or execution patterns. Supports both free tier (quick assessment) and premium tier (full 93-question assessment with detailed diagnostics).

This skill should be used when users want to train or fine-tune language models using TRL (Transformer Reinforcement Learning) on Hugging Face Jobs infrastructure. Covers SFT, DPO, GRPO and reward modeling training methods, plus GGUF conversion for local deployment. Includes guidance on the TRL Jobs package, UV scripts with PEP 723 format, dataset preparation and validation, hardware selection, cost estimation, Trackio monitoring, Hub authentication, and model persistence. Should be invoked for tasks involving cloud GPU training, GGUF conversion, or when users mention training on Hugging Face Jobs without local GPU setup.

Launch GStack Browser — AI-controlled Chromium with the sidebar extension baked in. Opens a visible browser window where you can watch every action in real time. The sidebar shows a live activity feed and chat. Anti-bot stealth built in. Use when asked to "open gstack browser", "launch browser", "connect chrome", "open chrome", "real browser", "launch chrome", "side panel", or "control my browser". Voice triggers (speech-to-text aliases): "show me the browser".

Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction.

Route web-game auto-playtesting with WAI Play (waiterve/wai-play): decide whether the next move is a testability check, authoring or repairing the `GameFlowAgentAPI` bridge, running a real browser playtest, reading the five-dimension quality report, or unblocking a key node the agent cannot reach. Use when the user wants an AI agent to actually play their HTML5 / canvas / vibe-coded web game and return reproducible evidence, scores, and fix suggestions across the five supported types (survivor-like, arcade shooter, platformer, puzzle/card, visual novel). Triggers on: wai-play, WAI Play, auto-playtest, AI plays my game, web game testing agent, GameFlowAgentAPI, GameFlowIntegration, jumpToScenario, game quality score, playtest evidence. Route Unity/Unreal frame-time work to `game-performance-profiler`, engine build failures to `game-build-log-triage`, human playtest notes to `game-demo-feedback-triage`, and generic browser automation to `browser-harness`.

Expert knowledge for Azure Oracle development including troubleshooting, security, configuration, and integrations & coding patterns. Use when configuring TDE with Key Vault, Oracle@Azure connectivity, AI DB VNets, Exadata log export, or Sentinel, and other Azure Oracle related development tasks. Not for Azure SQL Database (use azure-sql-database), Azure SQL Managed Instance (use azure-sql-managed-instance), SQL Server on Azure Virtual Machines (use azure-sql-virtual-machines), Azure VMware Solution (use azure-vmware-solution).

Verify an artifact that is about to leave the building — a partnership brief, pitch page, press release, customer email, RFP response, or any document sent to someone outside the org. Runs six checks before send — premise, confidentiality forward-test, evidence class, cold read by recipient personas, AI read, and tone metrics — and returns what to change with replacement copy. Use before sending anything outward-facing that carries customer detail, factual claims about a counterparty, or an ask.

Edit images with OpenAI GPT Image 2 (the `/edit` endpoint of ChatGPT Images 2.0) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents GPT Image Edit's strengths (preservation language, multilingual in-image text editing, multi-reference up to 10 images, layout / typography precision), the schema, and when to route to Nano Banana Edit / Flux Kontext / GPT Image 2 t2i instead. Calls `runcomfy run openai/gpt-image-2/edit` through the local RunComfy CLI. Triggers on "gpt image edit", "gpt-image-edit", "chatgpt image edit", "edit with gpt image 2", or any explicit ask to edit with this model.

Two-party working posture — user as director, agent as executor. Every fork, tradeoff, and taste choice is surfaced via batched AskUserQuestion with structural framing, a recommended default, and concrete previews when comparison is visual, so the human steers direction while the agent handles implementation. Eliminates the review-bottleneck (no giant diff to approve at the end — review is distributed across picks) and prevents codebase-understanding debt (the user remembers the architecture because they picked it). Use whenever the user invokes /duet, or says "work with me", "ask before", "check with me", "I want to decide", "don't assume", "human-in-the-loop", "co-author", "pair with me", "duet", or whenever a task clearly involves aesthetic, architectural, or irreversible strategic decisions — even without those exact words. Pair with the Duet output style to minimize cognitive load between picks.

Audits any draft against Built GTM voice rules and returns specific, line-level violations with rewrites. Not a general style critique. A rule-based QA check. Every violation gets a specific fix. Trigger on "check this", "does this sound like me", "voice check", "is this on brand", "review this draft", "what's wrong with this", "flag the AI tells in this", "make sure this sounds like me", or any request to audit a draft against Heath's Built GTM voice before publishing. Can be used on posts, articles, newsletter editions, comments, or any Built GTM content.

Interact with DeerFlow AI agent platform via its HTTP API. Use this skill when the user wants to send messages or questions to DeerFlow for research/analysis, start a DeerFlow conversation thread, check DeerFlow status or health, list available models/skills/agents in DeerFlow, manage DeerFlow memory, upload files to DeerFlow threads, or delegate complex research tasks to DeerFlow. Also use when the user mentions deerflow, deer flow, or wants to run a deep research task that DeerFlow can handle.

Edit images with Flux 1 Kontext Pro (Black Forest Labs' precise local image-edit model) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Flux Kontext's strengths (single-reference precise local edits, strong prompt control, consistent high-fidelity outputs), the schema (single image + prompt), and when to route to Nano Banana Edit / GPT Image 2 edit / Flux 2 Klein instead. Calls `runcomfy run blackforestlabs/flux-1-kontext/pro/edit` through the local RunComfy CLI. Triggers on "flux kontext", "flux-kontext", "flux 1 kontext", "kontext", "BFL kontext", or any explicit ask to edit with this model.

Designer's eye QA: finds visual inconsistency, spacing issues, hierarchy problems, AI slop patterns, and slow interactions — then fixes them. Iteratively fixes issues in source code, committing each fix atomically and re-verifying with before/after screenshots. For plan-mode design review (before implementation), use /plan-design-review. Use when asked to "audit the design", "visual QA", "check if it looks good", or "design polish". Proactively suggest when the user mentions visual inconsistencies or wants to polish the look of a live site. (gstack)

Expert knowledge for Azure Logic Apps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when building Logic Apps with SAP/IBM/FTP connectors, B2B/EDI flows, AI/OpenAI calls, XML/JSON transforms, or DevOps CI/CD, and other Azure Logic Apps related development tasks. Not for Azure Functions (use azure-functions), Azure API Management (use azure-api-management), Azure Service Bus (use azure-service-bus), Azure Event Grid (use azure-event-grid).

Import raw data (CSV, XLSX, TXT, or MATLAB tables) into formats used by Sensor Fusion and Tracking Toolbox. Handles both ground truth trajectories and sensor detection data. For truth: builds trackingScenarioRecording, tuning timetable, truthlog, or converted table. For sensor data: builds task-oriented dataFormat structs (preferred) or objectDetection arrays (legacy). Use when importing flight logs, GPS logs, radar detections, IR measurements, lidar/camera bounding boxes, ADS-B data, AIS ship tracks, or any recorded data for use with trackers, filter tuning, or tracker evaluation.

Simulates open quantum systems with QuTiP, the Quantum Toolbox in Python, solving Lindblad master equations (mesolve), Monte Carlo trajectories (mcsolve), and unitary dynamics (sesolve). Use when studying master-equation or Lindblad dynamics, decoherence, dissipation, quantum optics, cavity QED, or open-system time evolution. NOT for circuit-based quantum computing or hardware execution — for IBM Quantum circuits prefer alterlab-qiskit, for Google Quantum AI or NISQ circuits prefer alterlab-cirq, and for gradient-trained quantum ML prefer alterlab-pennylane. Part of the AlterLab Academic Skills suite.

Generate images with Google Nano Banana 2 (Gemini-family flash-tier text-to-image) on RunComfy — bundled with the model's documented prompting patterns so the skill gets sharper output than naive prompting against the same model. Documents Nano Banana 2's strengths (rapid iteration, in-image typography rendering, predictable framing, optional web-grounded context), the resolution-tier pricing, the safety-tolerance dial, and when to route to Nano Banana Pro / GPT Image 2 / Flux 2 / Seedream instead. Calls `runcomfy run google/nano-banana-2/text-to-image` through the local RunComfy CLI. Triggers on "nano banana", "nano-banana-2", "nano banana 2", "google image gen", "gemini image", or any explicit ask to generate with this model.

Create, validate, and consume Google's Open Knowledge Format (OKF) bundles — YAML-frontmatter Markdown files with type / title / description / resource / tags / timestamp fields for portable, interoperable AI-agent knowledge sharing. OKF formalizes the LLM-Wiki pattern into a vendor-neutral open specification so any producer can write and any agent can consume without translation. Routes: use `llm-wiki` for raw source capture + vault maintenance, `obsidian` for Obsidian-vault workflows, `graphify` for durable committed graphs, `scrapling` for web-content extraction into OKF docs. Triggers on: okf, open knowledge format, knowledge bundle, okf document, llm wiki standard, knowledge atom, agent context format, okf frontmatter, okf bundle, knowledge interoperability.