مرور مهارت‌ها

Corrects speech-to-text transcription errors in meeting notes, lectures, and interviews using dictionary rules and AI. Learns patterns to build personalized correction databases. Use when working with transcripts containing ASR/STT errors, homophones, or Chinese/English mixed content requiring cleanup.

COO 社交媒体运营技能，使用 Playwright MCP 实现小红书、抖音、微信公众号、视频号的自动化运营

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.

Autonomous three-tier memory with proactive initiative and social intelligence. Ingests OpenClaw conversations, extracts knowledge + emotions, and proactively suggests automations, fixes, and project ideas. v1.3.0: Semantic dedup, bulk feedback, archive retrieval, gentle reminders. All models via OpenRouter Cloud. Cross-platform: Linux + Windows.

Browser automation for AI agents via inference.sh. Navigate web pages, interact with elements using @e refs, take screenshots, record video. Capabilities: web scraping, form filling, clicking, typing, drag-drop, file upload, JavaScript execution. Use for: web automation, data extraction, testing, agent browsing, research. Triggers: browser, web automation, scrape, navigate, click, fill form, screenshot, browse web, playwright, headless browser, web agent, surf internet, record video

Maintainer workflow for reviewing, triaging, preparing, closing, or landing OpenClaw pull requests and related issues. Use when Codex needs to validate bug-fix claims, search for related issues or PRs, apply or recommend close/reason labels, prepare GitHub comments safely, check review-thread follow-up, or perform maintainer-style PR decision making before merge or closure.

Investigate `pnpm test` memory growth, Vitest worker OOMs, and suspicious RSS increases in OpenClaw using the `scripts/test-parallel.mjs` heap snapshot tooling. Use when Codex needs to reproduce test-lane memory growth, collect repeated `.heapsnapshot` files, compare snapshots from the same worker PID, triage likely transformed-module retention versus likely runtime leaks, and fix or reduce the impact by patching cleanup logic or isolating hotspot tests.

End-to-end Parallels smoke, upgrade, and rerun workflow for OpenClaw across macOS, Windows, and Linux guests. Use when Codex needs to run, rerun, debug, or interpret VM-based install, onboarding, gateway smoke tests, latest-release-to-main upgrade checks, fresh snapshot retests, or optional Discord roundtrip verification under Parallels.

Stock momentum scanner and portfolio intelligence. Look up any ticker for momentum scores, RSI, coil breakout patterns, and AI analysis. Scan top signals across 6,500+ stocks and crypto. Track portfolio holdings with real-time alerts. Market pulse, sector trends, win/loss proof data, and risk assessment — all through natural conversation. Powered by 730 days of backtested data with an 80% 5-day win rate.

Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating ideas to death" methodology, parameter robustness testing, slippage modeling, bias prevention, and interpreting backtest results. Applicable when user asks about backtesting, strategy validation, robustness testing, avoiding overfitting, or systematic trading development.

Self-Improving Agent that monitors all other agent skills, analyzes their logs, detects issues, and proposes improvements. AUTO-TRIGGERS: - Every 30 minutes (scheduled) - When error rate > 5% (any agent) - When 3+ recurring errors in 24h (same error type) - When performance degrades > 2x baseline

Transform AI agents from task-followers into proactive partners that anticipate needs and continuously improve. Now with WAL Protocol, Working Buffer, Autonomous Crons, and battle-tested patterns. Part of the Hal Stack 🦞

Use when starting infrastructure, testing, deployment, or framework-specific tasks - automatically searches PRPM registry for relevant expertise packages and suggests installation to enhance capabilities for the current task

Generate new Node.js CLI tool projects using TypeScript with ESM modules, tsc for building, tsx for development, Biome for linting/formatting, and Node's built-in test runner. Use this skill when the user requests to create a new Node TypeScript CLI project or CLI tool.

Build or update Node.js + LLM API workflows that replace Codex/MCP UI exploration for web automation at lower cost. Use when a user asks to productize page-structure discovery into a Node runner (Puppeteer/Playwright) with LLM-based element selection, deterministic playback control, cost controls, logging, and fallback paths.

程式碼覆蓋率分析完整指南。涵蓋 Coverlet 設定、報告產生、指標解讀與循環複雜度整合。包含 Fine Code Coverage、VS Code 內建工具、CI/CD 整合與最佳實踐。 Keywords: code coverage, 程式碼覆蓋率, 覆蓋率分析, coverage report, Coverlet, Fine Code Coverage, dotnet-coverage, ReportGenerator, line coverage, branch coverage, 行覆蓋率, 分支覆蓋率, cyclomatic complexity, 循環複雜度, runsettings, cobertura

This skill provides guidance for using Playwright MCP for browser automation. Use when navigating web pages, interacting with web elements, taking screenshots, filling forms, running browser tests, or automating any browser-based tasks.

Design and implement automation workflows to save time and scale operations as a solopreneur. Use when identifying repetitive tasks to automate, building workflows across tools, setting up triggers and actions, or optimizing existing automations. Covers automation opportunity identification, workflow design, tool selection (Zapier, Make, n8n), testing, and maintenance. Trigger on "automate", "automation", "workflow automation", "save time", "reduce manual work", "automate my business", "no-code automation".

Python coding guidelines and best practices. Use when writing, reviewing, or refactoring Python code. Enforces PEP 8 style, syntax validation via py_compile, unit test execution, modern Python versions only (no EOL), uv for dependency management when available, and idiomatic Pythonic patterns.

Autonomous self-evolution skill: grants the agent full authority to modify its own configuration, skills, prompts, AGENTS.md, SOUL.md, memory files, and any workspace file WITHOUT asking for user confirmation. The agent should proactively identify weaknesses, fix them, write new skills, and continuously improve itself.