Results for “e-e-a-t”

Model interpretability and explainability with SHAP (SHapley Additive exPlanations) — feature importance and plots (waterfall, beeswarm, bar, scatter, force, heatmap). Use when explaining ML model predictions, computing feature importance, debugging models, analyzing bias or fairness, comparing models, or implementing explainable AI across tree-based models (XGBoost, LightGBM, Random Forest), deep learning (TensorFlow, PyTorch), linear models, and any black-box model. Part of the AlterLab Academic Skills suite.

Executes a predefined implementation plan step by step, updating progress inline and running build or test commands.

`analysis-agent`/`task-agent`: use when commit timing, payloads, schema, ordering, idempotency, or retry changes; skip when no domain-event decision is required.

Automate Remarkety e-commerce marketing operations through Composio's Remarkety toolkit via Rube MCP.

Automate Zoho Mail tasks including email sending, folder and label management, and mailbox operations via Composio's Zoho Mail toolkit through Rube MCP.

Discovers and applies curated prompts from the prompts.chat collection to optimize AI interactions, prompt engineering, and workflow integration.

Transforms fuzzy problems into structured briefs that AI agents can reason about, critique, and act upon, while evaluating how much of the problem can be automated.

The two model-touching halves of Worklink, shipped as one opt-in skill. (1) Planner: decompose a parent Chainlink issue into testable worklink:ready leaf subissues (mutates Chainlink only, never executes). (2) Ready-queue poller: discovers worklink:ready leaves and dispatches them by invoking `mimir worklink run` as a detached subprocess, up to the concurrent-claim cap — it never reimplements claim/evidence/transition. Opt-in (mimirbot yes, muninn no): `mimir skills install chainlink-orchestrator`, then set the env below to enable autonomous dispatch.

Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right model for the user's actual intent — premium vocal hook, cheap background music library, multilingual pop song, repair a bad chorus, lengthen a 30 s draft into a 2 min cut — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate music", "make a song", "AI music", "background music", "instrumental track", "soundtrack", "jingle", "theme music", "royalty-free music", "compose", "music with lyrics", "extend music", "fix this song", "inpaint music", or any explicit ask to

Run a Codex prompt repeatedly on a fixed interval. Use for "/loop", "run this every N minutes/hours", "poll X every 5 minutes", "repeat this Codex prompt", or any recurring interval-based Codex job. This is the interval-repeat companion to the separate `schedule` skill (cron / specific-time). For a durable, always-on alternative that survives reboots and terminal exits, prefer Codex app Automations; this local CLI is a terminal fallback that only fires while its daemon process is running.

Create Earth2Studio diagnostic model wrappers for single-step data transformations, including simple derived diagnostics, packaged AutoModel diagnostics, and generative or diffusion diagnostics.

Expert en IoT avancé (MQTT, edge, device management, digital twin, security, DZ infrastructure)

Strategic business analyst and requirements expert. Use when the user asks to talk to Mary or requests the business analyst.

Strategic business analyst and requirements expert. Use when the user asks to talk to Mary or requests the business analyst.

Strategic business analyst and requirements expert. Use when the user asks to talk to Mary or requests the business analyst.

Integrate Azure OpenAI and OpenAI services in .NET applications for chat completions, embeddings, image generation, audio transcription, and assistants.

Make a web app agent-ready — propose a WebMCP tool manifest, integrate, verify in a real browser, heal; unrelated code stays untouched. Use for "webmcpify", "add WebMCP", or "expose app actions to AI agents".

Track and report token usage and estimated cost per session, agent, and phase

Write, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Covers the complete object model, coordinate system, measurement units, export workflows, and best practices.

Design multi-agent systems with context isolation, supervisor or swarm coordination, explicit handoffs, parallel execution, and decision frameworks for when multiple agents are justified.

Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right model for the user's actual intent — premium vocal hook, cheap background music library, multilingual pop song, repair a bad chorus, lengthen a 30 s draft into a 2 min cut — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate music", "make a song", "AI music", "background music", "instrumental track", "soundtrack", "jingle", "theme music", "royalty-free music", "compose", "music with lyrics", "extend music", "fix this song", "inpaint music", or any explicit ask to

Generate AI music on RunComfy via the `runcomfy` CLI — a smart router across the music-model catalog. Routes to ElevenLabs AI Music Generation (premium 44.1 kHz stereo vocal tracks, 5 s–5 min, $0.0083/s) and ACE Step / ACE Step 1.5 (StepFun-AI open-weights, tag-driven composition, multilingual lyrics, $0.0002–0.0003/s, ~27× cheaper), plus ACE Step audio-inpaint (regenerate a time range inside an existing track) and ACE Step audio-outpaint (extend a track before or after). Picks the right model for the user's actual intent — premium vocal hook, cheap background music library, multilingual pop song, repair a bad chorus, lengthen a 30 s draft into a 2 min cut — and ships each model's documented prompting patterns plus the minimal `runcomfy run` invoke. Triggers on "generate music", "make a song", "AI music", "background music", "instrumental track", "soundtrack", "jingle", "theme music", "royalty-free music", "compose", "music with lyrics", "extend music", "fix this song", "inpaint music", or any explicit ask to

Model software around the business domain using bounded contexts, aggregates, and ubiquitous language, with scoring and diagnostic tools for evaluating domain model quality.

Use when planning an EDBT project timeline across the multiple-cycle rolling model — choosing a submission cycle, backward-planning through the author-feedback phase and the in-cycle revise-and-resubmit window, and handling the cycle-to-conference roll — for a database-systems paper published open access on OpenProceedings.

Build real-time, bidirectional streaming applications with the Gemini Live API, covering WebSocket-based audio/video/text streaming, voice activity detection, function calling, session management, and ephemeral tokens.

Audit an existing financial model workbook for correctness (formula tracing, hardcode and error detection, sign and consistency checks, tie-outs, and sensitivity stress) before you rely on its outputs.

Provide graduated assistance from abstract conceptual nudge to concrete procedural step, with reflection required before each escalation. Teaches help-seeking as a skill and prevents direct-answer shortcuts.

Create a new AgentHub collaboration session with task, agent count, and evaluation criteria for multi-agent competitions.

Build automated evaluation pipelines for Python LLM applications using real LLM calls and structured test datasets.

Self-hosted web crawling and content extraction exposed as MCP tools, with depth control and clean markdown output.

Continuously monitors system performance, identifies improvement opportunities, and orchestrates skill discovery and creation to autonomously evolve capabilities.

Create or update reusable skills for this agent. Use this skill ONLY when the user asks to create a new skill, edit an existing skill, improve a SKILL.md, or capture a repeated workflow as a reusable skill. Do not use this skill for one-off tasks.

Instrument LLM applications with Langfuse for tracing, prompt versioning, evaluation, and dataset management across Python and JavaScript SDKs.

Master advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.

Computes derivatives, integrals, and solves calculus problems including optimization, Taylor series, and differential equations.

Pitfalls, examples, and edge cases for Hermes Kanban workers. The lifecycle itself is auto-injected into every worker's system prompt as KANBAN_GUIDANCE (from agent/prompt_builder.py); this skill is what you load when you want deeper detail on specific scenarios.