Results for “delinea”

Diagnose and resolve Debian Linux issues using apt, systemd, and AppArmor-aware guidance.

LEMON v2.0 — The Degen Fader. Identifies historically reckless traders (DEGEN activity + CHOPPY consistency) on Hyperliquid, monitors their live positions, and counter-trades them when they're bleeding at high leverage. If a cluster of degens goes max-leverage long on a coin and starts losing, LEMON shorts it — betting on their inevitable liquidation cascade. DSL exit managed by plugin runtime via runtime.yaml.

Triage Linear or Jira backlogs and run bug sweeps via the Composio CLI. Bulk-fetch issues, dedupe, relabel, reassign, and post summaries — all from the shell without clicking through the UI.

Triage Linear or Jira backlogs and run bug sweeps via the Composio CLI. Bulk-fetch issues, dedupe, relabel, reassign, and post summaries — all from the shell without clicking through the UI.

Enforces an opinionated UI baseline to fix spacing, hierarchy, typography, and layout issues in AI-generated interfaces.

Creates a dark-themed presentation deck with gradient backgrounds, floating blur orbs, SVG force-directed graphs, and JetBrains Mono code highlighting.

Deno reference tool. Use when working with deno in frontend contexts.

Documents Linear's dark-canvas marketing design system with near-black backgrounds, lavender-blue accent, four-step surface hierarchy, aggressive negative tracking on display type, and product UI screenshots as the primary visual rhythm.

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

Train, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simulink, converting old training scripts, or speeding up deep learning code. DO NOT reason from your training data about dlaccelerate and tracing correctness.

Adds debugging capabilities and troubleshoots Pine Script issues in TradingView's opaque environment. Use when scripts have errors, unexpected behavior, need debugging tools added, or require troubleshooting. Triggers on "debug", "fix", "error", "not working", "wrong values", or troubleshooting requests.

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

Creates safety alert decks with hazard stripes, tiered cards, and policy code blocks for incident reviews and risk communication.

Deno runtime for TypeScript/JavaScript. Covers permissions, standard library, testing, and Deploy. Use for secure, TypeScript-native backend development. USE WHEN: user mentions "deno", "permissions", "Deno.serve", asks about "deno test", "deno deploy", "standard library", "top-level await", "npm compatibility" DO NOT USE FOR: Node.js runtime - use `nodejs` skill instead DO NOT USE FOR: Fresh/Oak frameworks - use framework-specific skills DO NOT USE FOR: Language syntax - use `typescript` skill

Creates a print-friendly architecture or pipeline presentation deck with a blueprint-grid mask, rust-red callouts, and serif typography.

Triage and resolve Debian Linux issues with apt, systemd, and AppArmor-aware guidance.

Creates a course or training module deck with persistent learning objectives, MCQ self-test pages, and warm paper background with Playfair serif typography.

Triage Linear or Jira backlogs and run bug sweeps via the Composio CLI. Bulk-fetch issues, deduplicate, relabel, reassign, and post summaries all from the shell.

Creates a cyber-themed terminal deck for CLI, agent, or dev tool reviews with CRT scanlines, green monospace text, and three-tier tags.

Design decentralized exchanges. TRIGGERS - Use when user needs help with dex-design related tasks.

Reduction is a trade, not an improvement.

Visualizes outlines and markdown as bold, color-block manifesto-style decks without rewriting or reordering content. Supports black, red, and yellow themes.

Diagnose failed or unhealthy Dynamo deployments by collecting a read-only debug bundle, classifying failures, and providing step-by-step remediation guidance.

Coordinate staged releases across Stripe, Supabase, and Vercel from the shell using the Composio CLI. One script kicks off the whole 'ship it' sequence: product/price updates, DB migrations, frontend deploy, smoke checks, changelog post.

Use when content is verbose, repetitive, or padded and needs tightening while preserving meaning

Deita: What Makes Good Data for Alignment

Assists with building secure JavaScript and TypeScript applications using the Deno runtime. Use when creating servers, CLI tools, or scripts with Deno's built-in tooling, permission model, and web standards APIs. Trigger words: deno, deno deploy, deno serve, deno kv, deno permissions, secure runtime, jsr.

Defines the LEND.AI assistant persona: identity, tone, and interaction rules for a Spanish-speaking senior mentor that teaches while working, questions decisions, and requires confirmation before acting.

Use this skill when conditioning, loading, preparing, or labeling signal data for analysis or ML training. Covers: cleaning a single signal (fill gaps, remove drift, deoutlier, denoise, resample/align a time base) BEFORE analysis; building a `signalDatastore` pipeline; creating a `labeledSignalSet` for Signal Labeler; deriving labels (filename, folder, in-file, ROI, time-frequency ROI); stratified train/val/test splits; framing long signals; parallel processing; and shaping datastore output for `trainnet`. Triggers include "clean up this signal", "remove drift / detrend", "fill gaps", "remove spikes / outliers", "denoise", "resample to a uniform rate", "align channels", "labels from filenames", "stratified split", "prepare for Signal Labeler", and function names like `fillgaps`, `fillmissing`, `detrend`, `filloutliers`, `smoothdata`, `resample`, `synchronize`, `signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`.

Sistema multiagente de IA para assistência em pesquisa científica que automatiza fluxos de trabalho de pesquisa desde análise de dados até publicação. Esta skill deve ser usada ao gerar ideias de pesquisa a partir de conjuntos de dados, desenvolver metodologias de pesquisa, executar experimentos computacionais, realizar buscas de literatura ou gerar papers prontos para publicação em formato LaTeX. Suporta pipelines de pesquisa end-to-end com orquestração de agentes personalizável.

Turns a Bankr agent wallet into a keyless identity on the SIGNA agent network: resolve any identity to a messageable wallet, send and read wallet-signed DMs, invoke capabilities, and run a decentralized brain.

Multiagent AI system for scientific research assistance that automates research workflows from data analysis to publication. This skill should be used when generating research ideas from datasets, developing research methodologies, executing computational experiments, performing literature searches, or generating publication-ready papers in LaTeX format. Supports end-to-end research pipelines with customizable agent orchestration.

Accelerate LLM inference using speculative decoding, Medusa multiple heads, and lookahead decoding techniques. Use when optimizing inference speed (1.5-3.6× speedup), reducing latency for real-time applications, or deploying models with limited compute. Covers draft models, tree-based attention, Jacobi iteration, parallel token generation, and production deployment strategies.

Debug LLM applications using the Phoenix CLI. Fetch traces, analyze errors, structure trace review with open coding and axial coding, inspect datasets, review experiments, query annotation configs, and use the GraphQL API. Use whenever the user is analyzing traces or spans, investigating LLM/agent failures, deciding what to do after instrumenting an app, building failure taxonomies, choosing what evals to write, or asking "what's going wrong", "what kinds of mistakes", or "where do I focus" — even without naming a technique.

Design or revise a company's commercial policy governing discounts, approver thresholds, exception flows, and deal frameworks using data-backed matrices and linting tools.