Results for “fr”

Forecast any univariate time series (sales, sensors, energy, vitals, weather) zero-shot using Google's TimesFM foundation model, with point forecasts and prediction intervals from CSV, DataFrame, or array inputs.

Maps intrusion activity to the Lockheed Martin Cyber Kill Chain framework to identify adversary phase completion, detection gaps, and defensive controls for post-incident analysis and prevention.

Triages security incidents by classifying type, assigning severity based on business impact, enriching with threat intelligence, and routing to appropriate response teams using NIST SP 800-61r3 and SANS PICERL frameworks.

Parses Kubernetes API server audit logs (JSON lines) to detect exec-into-pod, secret access, RBAC modifications, privileged pod creation, and anonymous API access. Builds threat detection rules from audit event patterns.

Analyze Windows Security Event Logs to detect RDP brute force attacks by parsing Event ID 4625 and 4624 entries, identifying source IP frequency, and generating detection reports.

Triages and enriches indicators of compromise (IPs, domains, file hashes, URLs, email artifacts) from phishing emails, security alerts, or threat feeds, assigning confidence scores and dispositions using VirusTotal, AbuseIPDB, MalwareBazaar, and MISP.

Query AWS CloudTrail events with boto3, build statistical baselines of normal API activity, and detect anomalies such as unusual event sources, geographic anomalies, high-frequency API calls, and first-time API usage patterns.

Perform forensic acquisition and analysis of cloud storage services including Google Drive, OneDrive, Dropbox, and Box by collecting both API-based remote data and local sync client artifacts from endpoint devices.

Deploy Runtime Application Self-Protection (RASP) agents to detect and block attacks from within application runtime, covering OpenRASP integration, attack pattern detection, and security policy configuration for Java and Python web applications.

Create uncontested market space using value innovation instead of competing head-to-head. Covers the Four Actions Framework, Six Paths, strategy canvas, and buyer utility map.

Provides a single 0-100 cycle score blending VIX, SPY IV Rank, Put/Call ratio, and valuation percentile to determine offense vs. defense posture, based on Howard Marks' market cycle framework.

Write a user-centered problem statement that captures who is blocked, what they are trying to do, why it matters, and how it feels. Use when framing discovery, prioritization, or a PRD.

Evaluates US market bubble risk through quantitative data analysis using the Minsky/Kindleberger framework, scoring indicators like Put/Call ratio, VIX, margin debt, breadth, and IPO data.

Compresses AI agent output tokens by up to 65% using a terse, article-free communication style while preserving full technical accuracy. Supports multiple intensity levels and auto-disables for security warnings or ambiguous instructions.

Sweeps a codebase or UI for places that would genuinely benefit from motion, applying a strict gate to reject over-animation, and proposes precise animation recipes without implementing them.

Generates a gamified habit-tracking app UI with three phone frames: a cover poster, today's quests with XP and level bar, and a quest detail view with subtasks and rewards.

Analyzes ESLint configurations using the ESLint Node.js API and flat config system to detect rule conflicts, unused rules, and generate project-specific rule recommendations from eslint-plugin-unicorn and typescript-eslint.

High-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.

Builds detailed voice profiles for characters, narrators, brands, or AI agents, covering diction, syntax, rhythm, worldview, signature patterns, and failure modes, and can reverse-engineer profiles from writing samples or audit existing ones.

Guides founders through the fundraising lifecycle from pre-seed to Series B, covering stage benchmarks, an 8-week execution timeline, and preparation checklists for pitch decks, financial models, and data rooms.

Provides a complete deep-dive into Cross-Site Scripting (XSS) with exact payloads and bypass techniques for every PortSwigger lab variant, from apprentice to expert level.

Toolkit de alta performance para análise de intervalos genômicos em Rust com bindings Python. Use ao trabalhar com regiões genômicas, arquivos BED, tracks de cobertura, detecção de sobreposições, tokenização para modelos de ML, ou análise de fragmentos em genômica computacional e aplicações de aprendizado de máquina.

Process-based discrete-event simulation framework in Python. Use this skill when building simulations of systems with processes, queues, resources, and time-based events such as manufacturing systems, service operations, network traffic, logistics, or any system where entities interact with shared resources over time.

People leadership for scaling companies. Hiring strategy, compensation design, org structure, culture, and retention. Use when building hiring plans, designing comp frameworks, restructuring teams, managing performance, building culture, or when user mentions CHRO, HR, people strategy, talent, headcount, compensation, org design, retention, or performance management.

Builder of productized services, consulting packages, and agency offers. Use when creating service packages, consulting offerings, done-for-you services, agency service design, productized service, service delivery framework. Triggers: 'productized service', 'consulting package', 'agency offer', 'service packaging', 'done-for-you', 'DFY', 'service product'.

Technical architecture guide for building a multi-purpose consent preference center. Covers per-purpose granularity, easy withdrawal under Article 7(3), version history, audit trails, and IAB Transparency and Consent Framework v2.2 integration. Includes database schema, API design, and UI component specifications.

Consolidates project memory across harness and .memory/ with theme clustering, practical-expiry prune, ground-truth verify, and an adversarial second pass. Use when the user runs /memory:consolidate, asks to tidy/dedupe/prune memory, or reports redundant or stale memories. Also covers active writing during work.

Resolves GitHub issues using isolated worktrees and test-driven development, then delegates PR creation to /github:create-pr so the quality gate and the /github:review-pr loop always run. This skill should be used when the user asks to "resolve an issue", "fix issue

Fetch YouTube video transcripts and transform them into structured content (chapters, summaries, threads, blog posts). Use when the user shares a YouTube URL or video link, asks to summarize a video, requests a transcript, or wants to extract and reformat content from any YouTube video.

Write articles, guides, blog posts, tutorials, newsletter issues, and other long-form content in a distinctive voice derived from supplied examples or brand guidance. Use when the user wants polished written content longer than a paragraph, especially when voice consistency, structure, and credibility matter.

Deterministically score, route, rank, and select at most one fully vetted Pleasur.ai Stage 01 blog-keyword candidate using product-fit-dominant business value, traffic opportunity, brand fit, DR-relative winnability, and a free-seeker penalty. Use only after BID and AIO evaluation are complete.

Write clear, developer-friendly documentation — READMEs, API references, code comments, and changelog entries — tailored to the audience and the project's voice. Use when the user says "write docs", "document this API", "update the README", "add code comments", "changelog entry", or "explain this for contributors".

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.

Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.

Compress large language models using knowledge distillation from teacher to student models. Use when deploying smaller models with retained performance, transferring GPT-4 capabilities to open-source models, or reducing inference costs. Covers temperature scaling, soft targets, reverse KLD, logit distillation, and MiniLLM training strategies.