Results for “e-e-a-t”

Produces a complete narrated, subtitled, scored explainer video from a single topic prompt using a six-stage pipeline with script, voiceover, keyframes, animation, music, and local assembly.

Comprehensive guide for installing, configuring, operating, and troubleshooting OpenClaw — a self-hosted, multi-channel AI agent gateway. Use when the user asks about OpenClaw setup, configuration, channel management (WhatsApp/Telegram/Discord/Slack/iMessage/etc.), model provider setup, Gateway operations, multi-agent routing, security hardening, troubleshooting, or any maintenance task related to their local OpenClaw installation. Also use when encountering errors from `openclaw` CLI commands or the Gateway daemon.

Expert Haskell engineer specializing in advanced type systems, pure functional design, and high-reliability software. Use PROACTIVELY for type-level programming, concurrency, and architecture guidance.

Computes the InfoLM metric from torchmetrics for evaluating text generation against ground truth, with configurable information measures and sentence-level scoring.

润色中文学术论文，识别并替换模板化、机械化的AI表达，使文本更自然、更符合人类学者的写作习惯。

Expert en technologies agricoles avancées (precision farming, IoT sensors, satellite imagery, yield prediction, DZ context)

Walk through the manual-capture.md checklist for a slug, driving Chrome via the Claude in Chrome MCP to capture each visual that needs more than a static URL — multi-step flows, conversation states, settings panels, age gates on third-party sites. Runs equally well locally (your desktop Chrome) or on a VPS with always-on Chrome + the extension installed. Defaults to unattended mode when `BLOG_AGENT_AUTONOMOUS=1` (which forces `UNATTENDED=1`). Use after /generate-visuals has flagged action-shot or failed-screenshot entries.

Train, evaluate, export, quantize, and run inference on Mask2Former models for panoptic, instance, and semantic segmentation using NVIDIA TAO.

Fit statistical models (OLS, GLM, ARIMA, mixed models) with detailed diagnostics, residuals, and inference for econometrics and time series analysis.

Trains, evaluates, exports, prunes, quantizes, retrains, and runs inference for TAO OCRNet models for scene text recognition from cropped text-region images, supporting CTC and attention-based decoders.

Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)

Strategic search planning for agent-driven research. Generates structured search-term matrices with tiered fallback strategies, engine-specific operators, and grading criteria before executing any searches. Use this skill whenever research requires more than a single search query — comparing technologies, verifying claims across sources, surveying a landscape, investigating a multi-faceted question, or building evidence for a decision. Do NOT use for quick factual lookups, fetching a single known URL, or questions answerable from a single source. Covers tech, academic, regulatory, and general domains. Think of it as "research planning" — the matrix is the plan, execution comes after.

Designs and implements production-grade ML pipeline infrastructure: configures experiment tracking, creates orchestration DAGs, builds feature store schemas, deploys model registries, and automates retraining and validation workflows.

Implement iterative evaluation and refinement loops for AI agent outputs, using self-critique, evaluator-optimizer patterns, and rubric-based scoring to improve quality.

Analyzes prompts for safety, bias, security vulnerabilities, and effectiveness, providing detailed improvement recommendations with frameworks, testing methodologies, and educational content.

Reduces AI API costs by 30-75% by classifying task complexity, checking prompt quality, and routing tasks to the most cost-efficient model tier before execution.

Execute and analyze AI Data Poisoning attacks. By subtly injecting malicious or targeted misinformation into an LLM's training or fine-tuning dataset, an attacker can covertly manipulate the model's future outputs, implant backdoors, or enforce biases without altering the model architecture.

Designs and optimizes prompts for LLM-powered applications, covering system prompt architecture, context management, output formatting, and evaluation.

Guide for creating effective agent skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends the agent's capabilities with specialized knowledge, workflows, or tool integrations. Use when user says "create skill", "new skill", "build a skill", "update skill", or asks to make a reusable capability package.

Guides the creation of high-quality MCP servers that let LLMs interact with external services through well-designed tools, covering planning, implementation, testing, and evaluation.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

Read, create, and convert Microsoft PowerPoint (.pptx) presentations — extract slide text to JSON/markdown, build decks from JSON/markdown outlines, and export to PDF.

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks. Implements model serving, feature engineering, A/B testing, and monitoring.

Run end-to-end calibration on the bundled sample dataset against a running AMC microservice to verify the stack works before processing real data.

Quantifies audio source separation quality by computing the signal-to-distortion ratio (SDR) between ground-truth and estimated stems, with per-stem and record-level averaging.

Launches long-running evaluation batches in isolated tmux sessions with pre-flight verification, monitoring, and post-flight analysis for unattended runs.

Reference for building Tavily-powered search, extraction, crawling, and research into agentic workflows and RAG systems.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Evaluates the correlation between automatic text generation scores and human quality ratings, including robustness to domain and quality drift, using metrics like Kendall's Tau and Pearson correlation.

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

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

Automate Baselinker e-commerce operations through Composio's Baselinker toolkit via Rube MCP, with dynamic tool discovery and connection management.

Evaluates the naturalness, speaker similarity, and real-time synthesis speed of a Mandarin speech cloning system across diverse practical application scenarios.

Generate natural AI voices, text-to-speech, and voice synthesis using the inference.sh CLI with models like Inworld TTS, ElevenLabs, and Kokoro TTS for voiceovers, audiobooks, podcasts, and more.