Results for “fr”

Solves single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including constraint handling, Pareto front analysis, and benchmark problems.

Route security, compliance, privacy, crypto/Web3, framework security, vulnerability review, and risk prompts. Use when prompts mention security-review, security scans, bounty hunting, HIPAA, PHI, compliance, Web3 risk, smart contracts, x402, LLM trading risk, or framework-specific security.

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.

Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a vibration / biosignal / radar / sensor signal needing features for downstream ML or analysis. Includes optional GPU acceleration via canUseGPU and gpuArray. Does not cover filter design, audio-specific feature extraction (use audioFeatureExtractor in Audio Toolbox instead), batch dataset orchestration, or 2D / image features.

Extract embedded configuration from Agent Tesla RAT samples including SMTP/FTP/Telegram exfiltration credentials, keylogger settings, and C2 endpoints using .NET decompilation and memory analysis.

Runs a Node.js CLI that sends a question to three frontier LLMs in parallel, then synthesizes their responses into a single answer via an aggregator model, with paid and free tiers.

Formal evaluation framework for Codex sessions implementing eval-driven development (EDD) principles

Control cmux workspaces, panes, surfaces, and agent sessions safely from macOS terminal workflows.

Control cmux workspaces, panes, surfaces, and agent sessions safely from macOS terminal workflows.

Solve single- and multi-objective optimization problems with NSGA-II/III, MOEA/D, and other evolutionary algorithms, including Pareto front analysis, constraint handling, and benchmarking on standard test problems.

Evaluates the faithfulness of abstractive summaries by generating questions from summary sentences and verifying if the answers can be extracted from the source document, reporting Pearson and Spearman correlations with human judgments.

Benchmarks systems on the Abstraction and Reasoning Corpus (ARC) by requiring inference of abstract transformation rules from few input-output grid demonstrations and application to novel test cases, reporting the fraction of tasks solved.

Dynamic multi-agent workflows — plan first, then orchestrate parallel agents with adversarial verification via the local odw daemon. Use when the user asks for a "workflow", says "ultracode", or hands you a task spanning many files/items that benefits from parallel agents.

Live in-session delegation from Claude to Codex via the approval/delegation packet contract

Control cmux workspaces, panes, surfaces, and agent sessions safely from macOS terminal workflows.

Framework for building multi-agent conversation systems with customizable LLM-powered agents

Declarative programming framework for optimizing LLM prompts through compilation and automatic tuning

Formal evaluation framework for Claude Code sessions implementing eval-driven development (EDD) principles

Create or update the feature specification from a natural language feature description.

Compact the current conversation into a handoff document for another agent to pick up.

Predicts tissue or cell-type gene expression (log TPM and TPM) from a TSS-centered DNA sequence using the hosted Genomic Intelligence G0 Expression model, conditioned on a free-text cell-type description.

Before any explanation or answer, require the learner to produce a free-recall attempt and confidence rating. Use when a student wants help understanding or reviewing a topic — this skill ensures the AI works from what the learner already knows.

LangChain LLM application framework with chains, agents, RAG, and memory for building AI-powered applications

Decision-theoretic framework for agents embedded within the environments they model and act upon

Expert en prospection à froid (cold email, LinkedIn DMs, séquences personnalisées, délivrabilité)

Guides technology selection and implementation of AI and ML features in .NET 8+ applications using ML.NET, Microsoft.Extensions.AI, Microsoft Agent Framework, GitHub Copilot SDK, ONNX Runtime, and OllamaSharp.

Reviews a plan from a prior session by extracting the canonical reference prompt from seed/plan-reviewer-design.md and invoking the plan-reviewer agent with it, surfacing the verdict without auto-applying changes.

Generates game-ready sprite bundles from a text description, including character animations, 8-direction sprite sets, and exports to sprite sheets, manifest.json, Aseprite JSON, GIF/APNG, and individual PNG frames.

Extract a DDD-style ubiquitous language glossary from the current conversation, flagging ambiguities and proposing canonical terms. Saves to UBIQUITOUS_LANGUAGE.md. Use when user wants to define domain terms, build a glossary, harden terminology, create a ubiquitous language, or mentions "domain model" or "DDD".

DSPy declarative framework for automatic prompt optimization treating prompts as code with systematic evaluation and compilers

Quick project status report synthesized from state files, artifacts, and git activity. No agent dispatch (<2s).

BDI (Beliefs-Desires-Intentions) agency framework for designing autonomous agents with mental state architectures

Screens resumes with skill matching, experience evaluation, and bias-free candidate ranking

Globus CLI workflow for staging HuBMAP CODEX datasets from remote endpoints to HiPerGator

Fetch and display stored r(), e(), and s() results from the last Stata command.

Video outpainting on RunComfy via the `runcomfy` CLI — extend the spatial canvas of a video, change aspect ratio (9:16 vertical to 16:9 horizontal or vice versa), add environment beyond the original frame while preserving the central action. Routes prompt-shaped spatial extension through Wan 2-7 edit-video and points the agent at dedicated ComfyUI outpaint workflows when seam quality matters for hero delivery. Triggers on "video outpaint", "video outpainting", "extend video canvas", "expand video frame", "uncrop video", "aspect ratio change", "vertical to horizontal video", "16:9 from 9:16", "TikTok to YouTube", or any explicit ask to extend a video spatially beyond its original frame.