Results for “e-e-a-t”

Use when serving as a peer reviewer and deciding whether and how AI may assist, when a manuscript under review must never be pasted into an external tool, or when a confidentiality-preserving review and disclosure are needed.

Organizes Flutter code into domain, data, and presentation layers with unidirectional dependencies, using BLoC, use cases, and repository patterns for testable, maintainable enterprise applications.

Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always

Convert Java code to idiomatic C++. Use when migrating Java projects to C++, translating Java patterns to idiomatic C++, or refactoring Java codebases. Extends meta-convert-dev with Java-to-C++ specific patterns.

Convert Java code to idiomatic Rust. Use when migrating Java projects to Rust, translating Java patterns to idiomatic Rust, or refactoring Java codebases. Extends meta-convert-dev with Java-to-Rust specific patterns.

Convert Go code to idiomatic Rust. Use when migrating Go projects to Rust, translating Go patterns to idiomatic Rust, or refactoring Go codebases. Extends meta-convert-dev with Go-to-Rust specific patterns.

Launch distributed Megatron-LM training jobs on a SLURM cluster with a minimal sbatch skeleton, environment-variable setup for torch.distributed.run, CUDA_DEVICE_MAX_CONNECTIONS rules, container conventions, monitoring, and per-rank failure diagnosis.

This skill should be used when working with annotated data matrices in Python, particularly for single-cell genomics analysis, managing experimental measurements with metadata, or handling large-scale biological datasets. Use when tasks involve AnnData objects, h5ad files, single-cell RNA-seq data, or integration with scanpy/scverse tools.

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.

Guide users through a structured workflow for co-authoring documentation. Use when user wants to write documentation, proposals, technical specs, decision docs, or similar structured content. This workflow helps users efficiently transfer context, refine content through iteration, and verify the doc works for readers. Trigger when user mentions writing docs, creating proposals, drafting specs, or similar documentation tasks.

FLOW framework integration for bloggers. Evidence-led content workflow using the Find, Optimize, Win loop with stage-specific AI prompts from the FLOW knowledge base (30 blog-applicable prompts, CC BY 4.0). Use when user says "FLOW", "FLOW framework", "blog flow", "evidence-led blogging", "find optimize win", or wants stage-specific blog prompts.

Query the Cancer Dependency Map (DepMap) for cancer cell line gene dependency scores, drug sensitivity data, and gene effect profiles to identify cancer-specific vulnerabilities, synthetic lethal interactions, and validate oncology drug targets.

ML pipeline design — data versioning, experiment tracking, deployment patterns, drift monitoring. Use when building an ML pipeline from data to deployment, setting up MLOps tooling (DVC, MLflow, model registry), choosing deployment patterns (shadow, canary, A/B), or designing monitoring for drift and degradation.

Apple's approach to interface design and fluid, physical motion, translated for the web. Use when building or reviewing gesture-driven UI, spring animations, drag/swipe/sheet interactions, momentum and interruptible transitions, translucent materials and depth, typography (optical sizing, tracking, leading), reduced-motion, or the design foundations (feedback, spatial consistency, restraint) behind Apple-style interfaces. Also applies to any HTML-rendered output with interactive elements — investor decks, annual reports, product pages, slide presentations (Reveal.js, Guizang PPT), interactive documents, and landing pages that need premium feel beyond static aesthetics. Not for static Word/PDF generation (typography rules only).

Build throwaway code that answers exactly one design question — a tiny terminal app to feel out logic/state models, or several radically different UI variants switchable on one route. Use when the user wants to "prototype", "mock up", "sketch", "try a few versions", "see what it'd look like", "feel out this state machine", or is stuck choosing between designs they can only judge by seeing or driving them. Also used by the whiteboard skill for napkin-type tickets.

Use to measure which help articles actually resolve contacts versus merely being read, including contact-after-view and assisted resolution. Trigger for "are our help articles working", article view counts misleading, deflection measurement, contact after reading an article, self-service success metrics, KB ROI, or stopping AI agents from optimising for page views.

Run a source-grounded paid-advertising audit across major platforms including Google, Meta, YouTube, LinkedIn, TikTok, Microsoft, Apple, Amazon, Reddit, Pinterest, Snapchat, and X. Produces a versioned JSON audit bundle and human-readable reports with platform health scores, evidence coverage, and prioritized actions.

Guides the agent to reference official MathWorks Documentation and Help. Determine correct function syntax and workflows from user guides when deeper context is needed. Minimize iterations and repetitive trial and error. Use this skill to: Identify correct syntax and configuration details. Retrieve relevant, version-specific (or release-specific) information from official documentation. Consult user guides when conceptual or workflow context is needed. Apply best practices.

Turn engineering work into evidence-backed impact statements for performance reviews, self-reviews, promotion packets, and weekly updates by mining Copilot CLI session logs, git history, and GitHub PRs.

Manage Railway deployments - view logs, redeploy, restart, or remove deployments. Use for deployment lifecycle (remove, stop, redeploy, restart), deployment visibility (list, status, history), and troubleshooting (logs, errors, failures, crashes). NOT for deleting services - use railway-environment skill with isDeleted for that.

Collects Chinese A-share stock data, fetching stock lists and daily, weekly, and monthly K-line history into a local SQLite database for quantitative analysis.

Extract structured video metrics and channel information from YouTube by keyword search using the BrowserAct API, with no CAPTCHA or IP restrictions.

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.

Rowan is a cloud-native molecular modeling and medicinal-chemistry workflow platform with a Python API. Use for pKa and macropKa prediction, conformer and tautomer ensembles, docking and analogue docking, protein-ligand cofolding, MSA generation, molecular dynamics, permeability, descriptor workflows, and related small-molecule or protein modeling tasks. Ideal for programmatic batch screening, multi-step chemistry pipelines, and workflows that would otherwise require maintaining local HPC/GPU infrastructure.

Manage teams using Andy Grove's principles: production thinking for knowledge work, output indicators, managerial leverage, effective meetings, clean decisions, OKRs, and task-relevant maturity.

Expert knowledge for Azure DevOps development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when managing org/projects, Boards/work items, repos/pipelines, Analytics/OData/Power BI, or Azure DevOps Server, and other Azure DevOps related development tasks. Not for Azure Boards (use azure-boards), Azure Pipelines (use azure-pipelines), Azure Repos (use azure-repos), Azure Test Plans (use azure-test-plans).

Drafts a U.S. Customer Identification Program (CIP) policy compliant with USA PATRIOT Act Section 326 and 31 CFR 1020.220. Covers identity collection, verification, OFAC screening, CDD/beneficial ownership, recordkeeping, and governance. Trigger when the user needs to create or update a CIP policy, AML onboarding procedures, or exam-ready Section 326 documentation.

Generates and edits images and videos via fal.ai's queue-based API, supporting models like Flux, Gemini image, and Kling video-to-video, with automatic polling.

Design a document set for a document-based lesson — selecting and sequencing sources for analytical tension around a central question. Use when assembling sources for a new lesson or when an existing set produces flat responses.

Use to compare CX performance to a published or vendor benchmark without fooling yourself — scope mismatch, survivor bias, and definition mismatch usually make external benchmarks incomparable, and internal baselines often beat them. Trigger for "how do we compare to industry", "is our CSAT good", benchmark slide for the board, vendor benchmark report, "are we above average", outsourcing RFP benchmarks, or when someone cites a round-number industry standard.

Documents MariaDB-specific DROP TABLE syntax and behavior, including RESTRICT/CASCADE no-ops, DROP TEMPORARY TABLE, partial drops, IF EXISTS warnings, foreign key references, views, triggers, implicit commit, and WAIT/NOWAIT. Use when writing, generating, or reviewing DROP TABLE statements targeting MariaDB.

Validates agent outputs against schemas and quality criteria, scores confidence, detects hallucinations, monitors convergence, decides when to iterate, and synthesizes actionable feedback. Use when checking if a node's output is acceptable, scoring confidence, detecting fabricated content, deciding whether to re-execute, or generating improvement feedback. Activate on "validate output", "check quality", "confidence score", "hallucination check", "should we iterate", "improvement feedback". NOT for executing DAGs (use dag-runtime), planning DAGs (use dag-planner), or matching skills (use dag-skills-matcher).

World-class backend engineering - distributed systems, database architecture, API design, and the battle scars from scaling systems that handle millions of requestsUse when "backend, api, database, postgres, mysql, mongodb, redis, graphql, rest, authentication, authorization, caching, queue, background job, webhook, migration, transaction, n+1, rate limit, server, node.js, python, go, backend, api, database, architecture, performance, reliability, security" mentioned.

Expert knowledge for Azure Copilot development including troubleshooting, decision making, architecture & design patterns, security, configuration, and integrations & coding patterns. Use when sizing VMs, generating Bicep/Terraform, configuring Cosmos DB storage, or debugging App Service/VM disks, and other Azure Copilot related development tasks. Not for Azure AI services (use microsoft-foundry-tools), Azure Machine Learning (use azure-machine-learning), Azure AI Search (use azure-cognitive-search), Azure AI Bot Service (use azure-bot-service).

Build a fully automated AI-powered data collection agent for any public source — job boards, prices, news, GitHub, sports, anything. Scrapes on a schedule, enriches data with a free LLM (Gemini Flash), stores results in Notion/Sheets/Supabase, and learns from user feedback. Runs 100% free on GitHub Actions. Use when the user wants to monitor, collect, or track any public data automatically.

Sets up Microsoft Testing Platform hot reload to iterate fixes on failing tests without rebuilding, covering package installation, environment configuration, and the iterative workflow.