Results for “pe”

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Checks a GitHub, GitLab, or Perforce (p4) pull request (or merge request, or shelved changelist) for unresolved review comments, failing status checks, and incomplete PR descriptions. Waits for pending checks to complete, categorizes issues as actionable or informational, and optionally fixes and resolves them. Use when the user wants to check a PR/MR/CL, address review feedback, or prepare a change for submission.

Drafts an IRC §2702-compliant Qualified Personal Residence Trust agreement with safe harbor provisions under Rev. Proc. 2003-42 and Treas. Reg. §25.2702-5(c). Generates trust instrument, signature/notarization blocks, property exhibit, beneficiary schedule, and post-execution checklist. Use when drafting a QPRT for estate planning clients transferring a personal or secondary residence with a retained occupancy term to reduce gift tax valuation.

Mem0 Platform SDK for adding persistent memory to AI applications. TRIGGER when: user mentions "mem0", "MemoryClient", "memory layer", "remember user preferences", "persistent context", "personalization", or needs to add long-term memory to chatbots, agents, or AI apps. Covers Python SDK (mem0ai), TypeScript SDK (mem0ai), and framework integrations (LangChain, CrewAI, OpenAI Agents SDK, Pipecat, LlamaIndex, AutoGen, LangGraph). Also covers the open-source self-hosted Memory class. This is the DEFAULT mem0 skill for ambiguous queries. DO NOT TRIGGER when: user asks about CLI commands, terminal usage, or shell scripts (use mem0-cli), or Vercel AI SDK / @mem0/vercel-ai-provider / createMem0 (use mem0-vercel-ai-sdk).

Run a Virtual Think Tank — a structured multi-persona debate — before planning or making architectural/design/strategic decisions. Use this skill whenever the user is about to plan a system, make a technology choice, evaluate trade-offs, decide on an approach, or faces any decision where multiple perspectives would sharpen the outcome. Also trigger when the user says "think tank", "debate this", "perspectives on", "trade-offs", "should I use X or Y", "help me decide", "before we plan", or asks for pros/cons of competing approaches. This skill should run BEFORE any implementation planning begins — it produces a structured analysis that feeds into better plans.

Tool lifecycle UI components for React/Next.js from ui.inference.sh. Display tool calls: pending, progress, approval required, results. Capabilities: tool status, progress indicators, approval flows, results display. Use for: showing agent tool calls, human-in-the-loop approvals, tool output. Triggers: tool ui, tool calls, tool status, tool approval, tool results, agent tools, mcp tools ui, function calling ui, tool lifecycle, tool pending

Composite skill — full SEO + Accessibility audit of a website or webapp in one workflow. Chains audit-website (squirrelscan SEO + tech + perf scan) + seo-audit (SEO framing) + playwright-best-practices (axe-core a11y) + ui-audit (design-system accessibility patterns) → reconciled severity-ranked report split by SEO vs A11y vs Both. Use for periodic site health checks, pre-launch audits, or when search rankings drop.

Autonomous spec-driven development agent. Syncs DEV_SPEC.md into chapter-based reference files, identifies the next pending task from the schedule, implements code following spec architecture and patterns, runs tests with up to 3 auto-fix rounds, and persists progress with atomic commits. Use when user says "auto code", "自动开发", "自动写代码", "auto dev", "一键开发", "autopilot", or wants fully automated spec-to-code workflow.

Create new skills, modify existing ones, and measure their performance through iterative evaluation and benchmarking.

Provides a structured protocol for receiving and evaluating code review feedback, emphasizing technical verification over performative agreement.

Master Rust 1.75+ with modern async patterns, advanced type system features, and production-ready systems programming.

Design PostgreSQL schemas with best practices for data types, indexing, constraints, and performance patterns.

Create, run, configure, and review BenchmarkDotNet microbenchmarks for .NET code, covering project setup, comparison strategies, and cost-aware execution.

Generates immersive, high-performance web interfaces with advanced motion design, typography, and architectural craftsmanship.

Guides optimization of Qdrant query latency by tuning segments, memory, quantization, and search parameters.

Map AWS and Azure attack paths and find exploitable misconfigurations with CloudFox.

Audits fuzzy goals into checkable deliverables using Wittgenstein's philosophy of language, ensuring every word does work.

Destilliert aus eigenen NDAs einen Haltelinien-Standard mit Ampelmatrix und redigiert Gegenseite-Entwürfe chirurgisch per Word-Tracked-Changes.

Guides technical evaluation of code review feedback, emphasizing verification before implementation and reasoned pushback over performative agreement.

Adds a persistent memory layer that stores and retrieves user preferences and context across conversations using semantic search.

Tests approaches at extreme scales (1000x bigger/smaller, instant/year-long) to expose fundamental truths hidden at normal scales.

Logs daily development progress per project, fuses entries into a global diary, and syncs to Notion/Obsidian.

Provides quick reference documentation for Dnscheck concepts, best practices, and implementation patterns, covering intro, quickstart, debugging, performance, security, migration, and cheatsheet topics.

Runs a data augmentation pipeline on a given input and reports pass/fail per transform, diagnosing failures against known issues.

Embody the voice and methodology of Rumi to offer poetic, mystical guidance for emotional and spiritual struggles.

Embody B.F. Skinner's radical behaviorism to analyze behavior through operant conditioning and design reinforcement-based interventions.

Creates and manages AI agent teams for complex engineering tasks, with model routing, cost optimization, and performance evaluation.

Provides guidance on using Apache Spark RDDs, including creation, transformations, actions, and performance considerations.

Stores, retrieves, and curates persistent facts in a structured memory map, distinguishing between user facts and reference text.

Manages tmux sessions, windows, and panes for persistent terminal work and scriptable multi-pane layouts.

JNDI injection playbook. Use when Java applications perform JNDI lookups with attacker-controlled names, especially via Log4j2, Spring, or any code path reaching InitialContext.lookup().

One-time setup that gathers design context for your project and saves it to your AI config file. Run once to establish persistent design guidelines.

Postgres performance optimization and best practices from Supabase. Use this skill when writing, reviewing, or optimizing Postgres queries, schema designs, or database configurations.

Master modern SQL with cloud-native databases, OLTP/OLAP optimization, and advanced query techniques. Expert in performance tuning, data modeling, and hybrid analytical systems.

Fast DataFrame library (Apache Arrow). Select, filter, group_by, joins, lazy evaluation, CSV/Parquet I/O, expression API, for high-performance data analysis workflows.

Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick I/O, for microbiome analysis.