Results for “e-e-a-t”

Automate Zeplin design handoff tasks by discovering and executing tools through the Rube MCP interface.

Create, manage, and track PandaDoc documents, contacts, folders, templates, and webhooks directly from the terminal.

Read, send, and manage Gmail messages, threads, labels, and drafts through the Gmail API with managed OAuth authentication.

Replies to a Gmail message with automatic threading, optional attachments, HTML support, and draft saving.

Write or maintain technical documentation — READMEs, runbooks, API references, architecture docs — that a specific reader can act on without asking follow-ups.

Find sources for every numerical claim in the draft, add inline hyperlinks, and add internal links to brand-reference articles. Triggered after /draft.

Translates natural language data intents into syntactically valid Perfetto SQL queries and executes them against a local trace file using trace_processor.

Automate TripAdvisor content API operations through Composio's Rube MCP integration, including tool discovery, connection management, and execution.

Simula Elon Musk com profundidade psicológica e comunicacional, aplicando first principles thinking e raciocínio baseado em física para responder como o personagem.

Sovereign-grade safety OS for AI coding agents. 63 hooks, 2,025 skills, L1 memory, circuit breakers, and cross-engine enforcement — blocks rm -rf, force push, pipe-to-shell, and 40+ attack vectors before they reach your repo.

Use to find cancellation, downgrade and switching intent in support conversations, and to be honest about how much of your churn support can actually see. Trigger for "which customers are at risk of leaving", "find cancellation intent", "customers asking how to export their data", "top reasons customers asked to close their account", competitor mentions, or building a churn early-warning signal from support data.

Hardens Linux endpoints using CIS Benchmark recommendations for Ubuntu, RHEL, and CentOS to reduce attack surface, enforce security baselines, and meet compliance requirements.

Query real-time and historical equity market data—prices, news, financial statements, metrics, analyst estimates, insider and institutional activity, SEC filings, earnings press releases, segmented revenues, stock screening, and macro interest rates. Use when you need broad public-market research from a single AIsa-backed skill. Use when: the user needs market data, stock analysis, dividend research, or read-only financial data workflows.

Configure, deploy, and manage Senpi Trading Runtime (OpenClaw plugin @senpi-ai/runtime) for automated on-chain position tracking with DSL trailing stop-loss protection. Use when a user needs to create or modify runtime YAML files, configure DSL (Dynamic Stop-Loss) exit engine parameters (phases, tiers, time-based cuts), set up the position_tracker scanner to monitor a wallet's positions on Hyperliquid, install/list/delete runtimes via CLI, or inspect DSL-tracked positions. The runtime does NOT create strategy wallets; create/get the strategy wallet via Senpi MCP first, then link that existing wallet in runtime YAML. Triggers on mentions of senpi, Senpi runtime, DSL exit, stop-loss tiers, position tracker, trailing stop, openclaw senpi, dsl_preset, or strategy YAML configuration."

Use `analysis-agent` to analyze permissions, secrets, sensitive data, trust boundaries, and injection; `task-agent` to implement controls; and `review-agent` to assess evidence. Skip self-review and no-trust-impact work.

Design all 7 UI states for any data-dependent view: empty, loading, skeleton, partial, complete, error, offline. Use when asked about "loading state", "skeleton screen", "error message", "empty state", "optimistic UI", "what happens while data loads", or before marking any data-dependent view as done. Every view that fetches data must pass all 7 states before ship.

Builds, validates, schedules, and dynamically modifies DAG execution graphs. Decomposes problems into nodes with dependencies, performs topological sorting, detects cycles, resolves conflicts, and schedules wave-based parallel execution. Use when designing a DAG structure, validating dependencies, planning execution order, or modifying a DAG at runtime. Activate on "build DAG", "plan workflow", "DAG dependencies", "topological sort", "schedule execution", "modify DAG", "replan". NOT for executing DAGs (use dag-runtime), validating outputs (use dag-quality), or matching skills to nodes (use dag-skills-matcher).

Documents MongoDB's visual design system including colors, typography, layout, elevation, and shapes for UI implementation.

Lists Claude Code components such as skills, environment variables, sessions, settings, and tools, with options to research or display configured values.

Use CircleCI Chunk for AI-assisted CI/CD work through either the Chunk web UI or the chunk-cli. Trigger this skill when users ask to set up Chunk, troubleshoot or fix failing builds with Chunk, configure Chunk environments, schedule/proactively run Chunk tasks, or use chunk-cli commands such as init, validate, build-prompt, auth, sandbox, task, and skill install.

Design, implement, harden, and verify Model Context Protocol (MCP) servers with precise tool contracts, least-privilege authorization, safe transports, structured errors, and interoperability tests. Use when creating a new MCP server, exposing an API or data source through MCP, reviewing an MCP server design, adding or revising MCP tools, or preparing an MCP server for production.

Lazyweb is the design-evidence skill for AI coding agents. Use it when designing, critiquing, or changing product UI — it provides real app screenshots, competitor references, best practices, quick examples, creative cross-category ideas, paywall optimization guidance, and mobile growth + monetization A/B test context. Routes to the right Lazyweb mode (design workflow, quick search, update, flowchart, or A/B test research) using MCP tools and the Lazyweb server at https://www.lazyweb.com/mcp. Use before designing any screen when you need design evidence instead of training-data vibes.

Discovers and researches companies matching an ideal customer profile, using Browserbase Search API and a Plan→Research→Synthesize pattern to produce scored reports and CSV exports.

Itere em uma PR até que o CI passe. Use quando precisar corrigir falhas de CI, endereçar feedback de revisão, ou continuamente enviar correções até que todas as verificações fiquem verdes. Automatiza o ciclo de feedback-correção-push-aguardar.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Multi-agent collaboration plugin that spawns N parallel subagents competing on the same task via git worktree isolation. Agents work independently, results are evaluated by metric or LLM judge, and the best branch is merged. Use when: user wants multiple approaches tried in parallel — code optimization, content variation, research exploration, or any task that benefits from parallel competition. Requires: a git repo.

Help the user define a concrete, measurable goal before starting work, especially when they ask to use the goal tool, create a goal, set an objective, clarify success criteria, or turn a fuzzy intention into a quantitative outcome. Use this skill for goal creation and goal refinement only; it does not manage durable snapshots, decision logs, or long-running execution artifacts.

Guide users building apps, scripts, CI pipelines, or automations on top of the Cursor SDK - TypeScript (`@cursor/sdk`) or Python (`cursor-sdk` / `cursor_sdk`). Use when the user mentions integrating, installing, or writing code against the Cursor SDK; says `Agent.create`, `Agent.prompt`, `Agent.resume`, `agent.send`, `run.stream`, `run.messages`, `CursorAgentError`, `@cursor/sdk`, `cursor-sdk`, or `cursor_sdk`; asks to run Cursor agents programmatically from a script, CI/CD pipeline, GitHub Action, backend service, or other code outside the Cursor IDE; wants to pick between local and cloud runtime, configure MCP servers for an SDK agent, or handle streaming, cancellation, or errors; or is wiring Cursor into an automation, bot, or REST `/v1/agents` migration. Use eagerly rather than answering from memory; the SDK surface evolves and this skill is the source of truth for the external packages.

Lip-sync a face to a specific audio track on RunComfy via the `runcomfy` CLI. Routes across ByteDance OmniHuman (audio-driven full-body avatar from a portrait + audio), Sync Labs sync v2 / Pro (state-of-the-art mouth sync onto a video), Kling lipsync (audio-to- video and text-to-video with synced speech), and Creatify lipsync. The skill picks the right endpoint for the user's actual intent — portrait still + audio (avatar-style), source video + audio (mouth- swap on existing footage), or generate-and-sync from a script. Triggers on "lip sync", "lipsync", "make this video speak", "match audio to mouth", "dub video", "sync lips to voice", "Sync Labs", "voiceover sync", or any explicit ask to drive a face's mouth from an audio track.

Expert knowledge for Azure App Testing development including troubleshooting, best practices, decision making, architecture & design patterns, limits & quotas, security, configuration, integrations & coding patterns, and deployment. Use when running Azure Load Testing, Playwright Workspaces, JMeter/Locust tests, VNet/private endpoint tests, or CI/CD test pipelines, and other Azure App Testing related development tasks. Not for Azure Test Plans (use azure-test-plans), Azure DevOps (use azure-devops), Azure Pipelines (use azure-pipelines), Playwright Workspaces (use azure-playwright-workspaces).

Drafts ITAR Technology Control Plans (TCPs) for managing USML defense articles and technical data under 22 CFR Parts 120-130. Covers DDTC registration, classification, access controls, deemed export prevention, secure handling, training, audits, and incident response. Use when creating or updating export control compliance plans, technology control plans, or DDTC submission documents.

Interpretabilidade e explicabilidade de modelos usando SHAP (SHapley Additive exPlanations). Use essa skill ao explicar predições de modelos de machine learning, computar importância de features, gerar plots SHAP (waterfall, beeswarm, bar, scatter, force, heatmap), depurar modelos, analisar vieses ou justiça de modelos, comparar modelos ou implementar IA explicável. Funciona com modelos baseados em árvores (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), modelos lineares e qualquer modelo black-box.

Turn a segment into a multi-touch, multi-channel cadence that holds together. Steps, timing, channel, and the intent of each touch, tuned to who you are chasing. No 12 identical emails. Built for B2B SDRs and sales teams, customizable to your segment, channels, and sequencer. Trigger on "build an outbound cadence", "design a sequence", "how many touches over how many days", "multi-channel cadence for this segment", or any sequence design task.