AgentScope-AI

仅用于读取和总结文本类文件。文本格式优先使用 read_file；需要做类型探测时使用 execute_shell_command。PDF、Office、图片和压缩包由其他技能处理。

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Use this skill only for scheduled or recurring tasks. Manage jobs with qwenpaw cron list/create/get/state/pause/resume/delete/run, and always pass --agent-id explicitly.

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Answer user questions about QwenPaw installation and configuration: first locate and read local documentation, then distill the answer; if local information is insufficient, fall back to the official website documentation.

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当需要向更强 Agent 请求执行计划时使用；用于获取分步骤、可落地的计划，并由你自己执行，而不是让对方代执行任务。

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回答用户关于 QwenPaw 安装与配置的问题：优先定位并阅读本地文档，再提炼答案；若本地信息不足，兜底访问官网文档。

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Read and summarize text-based file types only. Prefer read_file for text formats; use execute_shell_command for type detection when needed. PDF/Office/images/archives are handled by other skills.

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Deterministic handbook-grounded retrieval and thermocouple computations for reflow profile compliance outputs such as ramp, TAL, peak, feasibility, and selection.

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Automated Planning utilities for loading PDDL domains and problems, generating plans using classical planners, validating plans, and saving plan outputs. Supports standard PDDL parsing, plan synthesis, and correctness verification.

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Solving finite-horizon LQR via dynamic programming for MPC.

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Adding integral action to MPC for offset-free tension tracking.

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Selecting MPC prediction horizon and cost matrices for web handling.

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Linearizing nonlinear dynamics around operating points for control design.

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Align Python version and repo-declared dependencies (requirements.txt / environment.yml) before installing packages for NLP research code reproduction.

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Build unified multi-level category taxonomy from hierarchical product category paths from any e-commerce companies using embedding-based recursive clustering with intelligent category naming via weighted word frequency analysis.

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Comprehensive spreadsheet creation, editing, and analysis with support for formulas, formatting, data analysis, and visualization. When Claude needs to work with spreadsheets (.xlsx, .xlsm, .csv, .tsv, etc) for: (1) Creating new spreadsheets with formulas and formatting, (2) Reading or analyzing data, (3) Modify existing spreadsheets while preserving formulas, (4) Data analysis and visualization in spreadsheets, or (5) Recalculating formulas

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AI驱动的Java代码安全审计技能，实现系统化、高覆盖率的漏洞挖掘。使用场景： (1) 审计Java/Kotlin项目寻找安全漏洞（0day挖掘、代码审计、安全评估） (2) 企业级代码库的安全审计（支持大型项目） (3) 需要高质量、低幻觉率的安全审计报告 (4) CI/CD集成的前期漏洞发现 触发关键词：Java审计、代码审计、安全审计、漏洞挖掘、0day、安全评估、Java security audit、code review for security

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Extract locational marginal prices (LMPs) from DC-OPF solutions using dual values. Use when computing nodal electricity prices, reserve clearing prices, or performing price impact analysis.

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Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .csv, or .tsv file (e.g., adding columns, computing formulas, formatting, charting, cleaning messy data); create a new spreadsheet from scratch or from other data sources; or convert between tabular file formats. Trigger especially when the user references a spreadsheet file by name or path — even casually (like "the xlsx in my downloads") — and wants something done to it or produced from it. Also trigger for cleaning or restructuring messy tabular data files (malformed rows, misplaced headers, junk data) into proper spreadsheets. The deliverable must be a spreadsheet file. Do NOT trigger when the primary deliverable is a Word document, HTML report, standalone Python script, database pipeline, or Google Sheets API integration, even if tabular data is involved.

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Redact text from PDF documents for blind review anonymization

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Analyzes 3D mesh files (STL) to calculate geometric properties (volume, components) and extract attribute data. Use this skill to process noisy 3D scan data and filter debris.

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Use this skill when reading sensor data from CSV files, writing simulation results to CSV, processing time-series data with pandas, or handling missing values in datasets.

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Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.

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Fit first-order dynamic models to experimental step response data and extract K (gain) and tau (time constant) parameters.

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Calculate PI/PID controller gains using Internal Model Control (IMC) tuning rules for first-order systems.

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