Results for “pe”

peter — 技能索引

php84-performance

Performance — Forge Skill

Performance Profiler

Perl Security

ML / research person pack for Content Factory. Use when the user says person ml, @person-ml, ML person, research scientist person, or LLM researcher person. Auto-loads ml-research-engineer, llm-researcher, ai-research-scientist plus experiment-tracking, evaluation, cf-llm-model-usage.

WordPress Performance Review

acl-permission-system

Drafts a U.S. Lis Pendens (Notice of Pending Action) for recording against real property. Covers intake, statutory authority mapping, legal description, verification, and proof of service. Use when preparing a lis pendens, notice of pending action, or recording notice tied to title or possession claims. Trigger: lis pendens, notice of pending action, quiet title, specific performance, foreclosure, partition, lien enforcement, expungement.

Generate data-driven user personas for UX research and product design. Usage: /persona generate [options]

Feishu permission management for documents and files. Activate when user mentions sharing, permissions, collaborators.

Systematically investigate all persistence mechanisms on Windows and Linux systems to identify how malware survives reboots and maintains access.

Create refined user personas from research data — 3 personas with JTBD, pains, gains, and unexpected insights. Use when building personas from survey data, creating user profiles from research, or segmenting users for product decisions.

Modern Perl 5.36+ idioms, best practices, and conventions for building robust, maintainable Perl applications.

Modern Perl 5.36+ idioms, best practices, and conventions for building robust, maintainable Perl applications.

Modern Perl 5.36+ idioms, best practices, and conventions for building robust, maintainable Perl applications.

Analyzes Perfetto traces to find the root cause of latency, memory, or jank issues in Android apps.

Personal protective equipment tracker. Use when json ppe tasks, csv ppe tasks, checking ppe status.

Browse PeerTube federated video from the terminal: view videos and channels, search across instances, check server stats, and manage your account. Uses OAuth2 authentication with token persistence. Use when the user mentions PeerTube, federated video, decentralized video platforms, or browsing/uploading to a PeerTube instance.

Migrate Pester v5 classic Should -Be assertion syntax to the new Pester v6 Should-* operators with a step-by-step mapping and behavioral gotchas.

Automate Perigon operations through Composio's Perigon toolkit via Rube MCP, with tool discovery and connection management.

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

PTES-aligned adversarial security audit for backend, frontend, and mobile applications. Produces a CVSS-scored Hacker Report with verified PoCs and phased remediation.

Fine-tune large language models by training less than 1% of parameters using LoRA, QLoRA, and 25+ adapter methods, enabling efficient adaptation on consumer GPUs.

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

Comprehensive guide to bpe. Master the concepts, implementation, best practices, and real-world applications of bpe in professional environments.

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

Performance-coaching mode for repeated failures, passive behavior, completion-quality issues, or explicit try-harder requests. Uses structured troubleshooting and evidence-first delivery habits.

Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train <1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.

Progressive Web App development with Service Workers, offline support, and app-like behavior. Use for caching strategies, install prompts, push notifications, background sync. Activate on "PWA", "Service Worker", "offline", "install prompt", "beforeinstallprompt", "manifest.json", "workbox", "cache-first". NOT for native app development (use React Native), general web performance (use performance docs), or server-side rendering.