Results for “e-e-a-t”

Delegates tasks to specialized AI agents running in parallel via the Box0 platform, enabling code review, security checks, research, and documentation.

Use when creating hooks for Claude Code plugins. Covers hook events, configuration, exit codes, and stdin/stdout contracts. Hooks execute in response to events to validate operations and enforce policies.

You are an expert technical writer creating comprehensive project documentation. Your goal is to write a README.md that is absurdly thorough—the kind of documentation you wish every project had.

End-to-end Kaggle competition workflow for scored submissions, covering code competitions, validation, metrics, public notebook/discussion intel, tabular/text/image modeling, tuning, ensembling, multi-notebook architectures, Kaggle GPU offload, and hidden-test debugging.

Drafts enforceable End-User License Agreements for software licensors across desktop, mobile, SaaS, and cloud models. Covers click-wrap formation, IP ownership, liability limitations, data privacy compliance (GDPR/CCPA/COPPA), and export controls. Use when drafting software license agreements, app store terms, SaaS subscription agreements, or trial/freemium license terms.

Guides users through ECC's components and installation by inspecting the live repository before answering.

Adopts the conversational style and interview techniques of Joe Rogan for engaging, accessible discussions of complex topics.

Read artifacts from the shared bench — the workspace where desks leave findings, verdicts, and work products for each other and the operator.

Assess the test suite of a codebase — where tests are missing, where they exist but are weak, and which gaps actually matter. Use this skill whenever the user asks about test coverage, test quality, "are there enough tests", "where should we add tests", testing gaps, test debt, untested code paths, flaky tests, or generally wants to know whether a codebase is well-tested. Trigger even on casual phrasings ("is this tested?", "what's the test situation?", "audit our tests"). This skill does NOT write tests — it only assesses what exists and identifies what's missing. For test generation, this is the wrong skill.

Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 / Table 2 / event-study figure / robustness gauntlet — OR in epidemiology / public health style (target-trial emulation, IPTW + g-formula + TMLE triplet, Mendelian randomization, KM/AFT survival, E-value sensitivity, STROBE/TRIPOD reporting) — OR in ML causal inference style (DML, S/T/X/R/DR meta-learners, causal forest, Dragonnet/TARNet/CEVAE, BCF, CATE distribution, policy learning, conformal causal, fairness audit, causal discovery) — OR in distributional / gap-decomposition style (Oaxaca–Blinder `sp.oaxaca`, Kitagawa `sp.kitagawa_decompose`, DiNardo–Fortin–Lemieux `sp.dfl_decompose`, Gelbach `sp.gelbach`, Fairlie `sp.fairlie`, RIF / FFL `sp.rif_decomposition`, all reachable through the `sp.decompose` dispatcher). Also covers exporting mu

Automate Mailersend email operations through Composio's toolkit via Rube MCP, with tool discovery and connection management.

Ingest, index, search, and edit video and live streams with timestamps, subtitles, overlays, and real-time alerts.

Build self-serve acquisition and expansion motions, including deciding between PLG and sales-led, optimizing activation, driving freemium conversion, and building growth equations.

Comprehensive real estate agent assistant for buyer representation, seller representation, listing management, offer negotiation, transaction coordination, and closing support — delivering a world-class client experience from first showing to final closing across residential and investment real estate

Scaffold the local env file with required variable stubs from .env.example and code, open it for the user to fill, and verify completeness by key names only — never reading secret values

Searches global company registrations via OpenCorporates and SEC EDGAR, offering tools to find companies, retrieve details, and locate SEC filings.

Control LG smart appliances via ThinQ API. Use when user asks about their fridge, washer, dryer, AC, or other LG appliances. Supports checking status, changing temperature, toggling modes (express, eco), and monitoring door status.

Transforms Chan Theory technical analysis into an executable, reproducible research workflow with strict level, structure, and invalidation gates for A-shares, Hong Kong stocks, ETFs, indices, and futures. For research and study only; never issues stock tips or promises returns.

Interact with Moltbook social network for AI agents. Post, reply, browse, and analyze engagement. Use when the user wants to engage with Moltbook, check their feed, reply to posts, or track their activity on the agent social network.

Experimental methodology and statistical rigor specialist. Use when the user asks to talk to Breach, requests the methodologist, or needs experiment design review, ablation planning, and reproducibility protocols.

Create and maintain Actor entities — humans and AI agents that participate in the project. Use when adding a new collaborator (human or agent) to the project, updating their preferences/expertise, or querying who does what.

Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.

Generate and edit videos using the Gemini Omni Flash model: text-to-video, image-to-video, video editing, and turn-by-turn refinement via the official google-genai SDK.

LLaVA-OneVision: Easy Visual Task Transfer

Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.

Guides OLTP database schema design through six stages: domain and access patterns, entities and relationships, keys and constraints, normalization trade-offs, indexing and performance, and operations and evolution. Includes a final review checklist and tips for effective guidance.

Personal finance review skill for individuals who want to understand their spending, budgets, and financial patterns. Use whenever the user wants to analyze expenses, categorize spending, review a budget, build a budget from scratch, analyze debt, audit subscriptions, understand their savings rate, or track progress toward a financial goal. Triggers: "help me review my spending", "here are my expenses", "can you look at my budget", "help me build a budget", "I want to understand where my money goes", "categorize these transactions", "help me pay off my debt", "audit my subscriptions", "am I saving enough", "am I on track for my goal", "analyze my finances", or any time the user shares financial data (even raw or messy) and wants insight. Does NOT provide investment, tax, or financial planning advice — helps users understand their own data. Trigger proactively when the user pastes transactions, expenses, or any money-related data, even without an explicit request for analysis.

Plan, promote, run, and optimize webinars and virtual events to generate and convert demand, from registration through follow-up.

Defines a design system for ElevenLabs with colors, typography, layout, and component tokens for building brand-consistent interfaces.

Design a worked example fading sequence from fully worked examples through to independent practice. Use when teaching procedures, algorithms, or multi-step processes to novice learners.

Enforces strict outside-in red-green-refactor TDD with one-failure-per-turn discipline, predicting failures before every run, hardcoding minimum changes, and using triangulation and property-based testing. Triggers on explicit TDD requests and tasks phrased as 'implement', 'add', 'write a function', 'build a feature'.

Ingests EPUB and ebook files into a local vector index and provides a command-line interface for asking questions about the books.

DAO Architect IA — Expert en architecture DAO (governance, proposals, voting mechanisms, treasury management)

Detect and respond to unauthorized cryptocurrency mining in AWS and Azure environments using cost anomalies, compute utilization, network traffic analysis, and runtime monitoring.

Diagnose whether an AI workflow suffers from context stuffing or benefits from context engineering, and apply structured techniques to improve reliability.

Generates unit tests, integration tests, and E2E tests for React/Next.js applications by scanning components, analyzing coverage reports, and scaffolding Playwright test files.