Agent Skills

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name: math-modeling

description: 当用户要求数学建模、建模竞赛、建模分析、代码求解、结果可视化或生成数学建模论文时使用。支持完整三阶段流程、单独执行任一角色，以及在关键节点使用独立 Subagent 进行阶段内质检；默认只启用质检 Subagent，用户可明确选择额外协作。

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name: pdf

description: Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

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name: pdf

description: Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating new PDFs, filling PDF forms, encrypting/decrypting PDFs, extracting images, and OCR on scanned PDFs to make them searchable. If the user mentions a .pdf file or asks to produce one, use this skill.

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name: 双引擎论文搜索

description: 使用 OpenAlex 与 AnySearch 两个真实数据源并行搜索、交叉匹配和输出可追溯论文元数据。

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name: 双引擎论文搜索

description: 使用 OpenAlex 与 AnySearch 两个真实数据源并行搜索、交叉匹配和输出可追溯论文元数据。

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name: 建模手

description: 数学建模的题目理解、模型选择和算法设计阶段。输出题目分析报告与术语表格。

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name: 建模手

description: 数学建模的题目理解、模型选择和算法设计阶段。输出题目分析报告与术语表格。

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name: 科研可视化工具

description: 从数据剖析到出版级成图的完整可视化工具。先做数据剖析（列类型/样本量/分布/异常值/分组结构/相关性）， 再结合论证目标推荐图型，主动拦截科研画图经典错误，产出 Nature / Science / IEEE / Elsevier / PNAS / 中文核心期刊级别的成图。覆盖数据 EDA、图表契约、选图决策、出版级绘制、程序自检 + AI 读图闭环、多格式 导出和文件审计。数学建模场景额外支持三类图体系（原始数据/过程/结果）、子问题覆盖检查和建模流程图规范。 当用户涉及论文配图、科研画图、数据可视化、选图、期刊投稿图、figure、出版级图表、matplotlib、seaborn、 plotly、误差棒、显著性标注、色盲安全配色、矢量图导出、中文论文图表、多面板时使用。

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name: 科研可视化工具

description: 从数据剖析到出版级成图的完整可视化工具。先做数据剖析（列类型/样本量/分布/异常值/分组结构/相关性）， 再结合论证目标推荐图型，主动拦截科研画图经典错误，产出 Nature / Science / IEEE / Elsevier / PNAS / 中文核心期刊级别的成图。覆盖数据 EDA、图表契约、选图决策、出版级绘制、程序自检 + AI 读图闭环、多格式 导出和文件审计。数学建模场景额外支持三类图体系（原始数据/过程/结果）、子问题覆盖检查和建模流程图规范。 当用户涉及论文配图、科研画图、数据可视化、选图、期刊投稿图、figure、出版级图表、matplotlib、seaborn、 plotly、误差棒、显著性标注、色盲安全配色、矢量图导出、中文论文图表、多面板时使用。

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name: 编程手

description: 数学建模的 Python 或 MATLAB 实现、运行、表格输出、可视化和复现阶段。

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name: 编程手

description: 数学建模的 Python 或 MATLAB 实现、运行、表格输出、可视化和复现阶段。

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name: 论文手

description: 根据题目、建模分析和真实代码结果生成完整 Word 数学建模论文，用户显式要求时同时生成 LaTeX 论文。

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name: 论文手

description: 根据题目、建模分析和真实代码结果生成完整 Word 数学建模论文，用户显式要求时同时生成 LaTeX 论文。

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name: beautify-github-readme

description: Redesign GitHub README homepages or create project-native pure SVG, hybrid SVG-composed PNG/WebP, and opt-in animated GIF assets. Use when a user asks to beautify, redesign, rebrand, visually upgrade, simplify, or audit a GitHub README; create only a hero, section headers, diagrams, badges, motion graphics, showcase modules, or other README assets; or turn a repository homepage into a cohesive visual story. If whole-README work versus asset-only work is unclear, ask which scope the user wants. For hero-like assets where pure SVG and generated raster material are both viable, explain the tradeoffs and confirm the implementation before creating the asset.

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name: talk-normal

description: Stop LLM slop. A curated system prompt that cuts verbose, corporate-sounding LLM output by 56-71% (measured) while preserving information. Works bilingually (English + Chinese). Installs into your AGENTS.md as an always-on behavior modifier.

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name: talk-normal

description: Stop LLM slop. A curated system prompt that cuts verbose, corporate-sounding LLM output by 56-73% (measured) while preserving information. Works bilingually (English + Chinese). Installs into your AGENTS.md as an always-on behavior modifier.

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name: metabigor

description: Use when operating the metabigor CLI for OSINT recon and infrastructure mapping without API keys. Covers finding network ranges from an ASN, org, domain, or IP (net); enumerating subdomains from certificate logs (cert); enriching IPs with ports/CVEs via Shodan InternetDB (ip); searching public GitHub code for secrets and subdomains (github); clustering IPs by ASN (cluster); pivoting to related domains via crt.sh/WHOIS/analytics (related); detecting CDN/WAF vendors and isolating candidate origins (cdn); collecting archived URLs and WARC-mined endpoints (url); refreshing the offline databases (update); and chaining these commands into a recon pipeline.

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name: agent-dispatch

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name: architecture-design

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name: architecture-patterns

description: System and API design guidance covering component boundaries, data flow, integration patterns, and scalability considerations.

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name: assimilate-popular-workflows

description: This skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositories for extractable processes, babysitter plugins, and reusable procedural insights. Searches GitHub for SKILL.md files, classifies repos by archetype, and maintains structured research under docs/reference-repos/.

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name: atlas

description: Atlas turns your STATED NEED into a real systems atlas by SCANNING your actual sources (Azure via `az`, git repos, local dirs) and process/data mining them, THEN enriching against the Atlas knowledge graph. Use this skill when asked to inventory/map your real systems, scan your cloud + repos + directories, mine the real processes or data they contain, or collect their real constraints/gotchas. (atlas, scan my systems, inventory our azure account, map my repos, real systems atlas, process mining, data mining, collect nuances, system discovery)

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name: atlas-graph-query

description: Reference for querying the Atlas knowledge graph through its MCP tools — the SECONDARY enrichment/comparison layer that adds best-practice context to systems you have ALREADY scanned from your real sources (`az`, repos, dirs). Use when you need to look up nodes, edges, kinds, clusters, stats, or wiki pages in Atlas to compare against your real inventory. (atlas graph, query atlas, atlas mcp, search the graph, graph neighbors, atlas record, atlas kinds, enrichment layer)

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name: attention-variants-from-papers

description: Implement paper-defined attention variants by extracting mechanism invariants, mapping tensor shapes, preserving module interfaces, validating numerical behavior, and integrating the custom attention into an existing transformer stack.