建模手
建模手 guides mathematical modeling workflows by systematically analyzing problem statements, identifying constraints and data requirements, then recommending tailored model approaches. It produces structured analysis reports and terminology tables to support the model selection and algorithm design phases before implementation begins.
建模手 skill helps you analyze mathematical modeling problems and select appropriate models for solution design.
AI-generated summary based on this skill's SKILL.md
Decision gist · record as of 2026-07-25
建模手 skill helps you analyze mathematical modeling problems and select appropriate models for solution design. 建模手 guides mathematical modeling workflows by systematically analyzing problem statements, identifying constraints and data requirements, then recommending tailored model approaches. It produces structured analysis reports and terminology tables to support the model selection and algorithm design phases before implementation begins.
Use it when
- 建模手 works by taking your problem statement as input and conducting systematic analysis.
- 建模手 offers comprehensive modeling support within XiaoMaColtAI's ecosystem.
Install
XiaoMaColtAI/math-modeling-skill/建模手 · repository language: Python
generated, unverified - the skill's exact subdirectory could not be determined; check the repository on GitHub
Open directory. Skills are indexed for reading, not audited. Review a skill's body before installing it.
Frequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
What is 建模手 and how does it support AI agent modeling?
建模手 is a skill designed to guide mathematical modeling workflows for AI agents. It systematically analyzes problem statements, identifies constraints and data requirements, then recommends tailored model approaches. The skill produces structured analysis reports and terminology tables to support model selection and algorithm design phases before implementation begins.
How do I use 建模手 for automated model construction?
建模手 works by taking your problem statement as input and conducting systematic analysis. It identifies key constraints, data requirements, and recommends appropriate modeling approaches. The skill generates structured analysis reports and terminology tables that guide you through model selection and algorithm design, streamlining the construction process before you move to implementation.
What are the main capabilities of 建模手 for XiaoMaColtAI?
建模手 offers comprehensive modeling support within XiaoMaColtAI's ecosystem. Its core capabilities include problem statement analysis, constraint identification, data requirement mapping, model approach recommendations, structured report generation, and terminology table creation. These features enable agents to systematically work through the planning and design phases of mathematical modeling projects.
Can 建模手 be integrated into my existing agent workflow?
Yes, 建模手 is designed as a skill that integrates into agent workflows. It functions as a specialized tool for the modeling phase, accepting problem inputs and delivering structured analysis outputs. You can incorporate it into your workflow to handle the systematic analysis and model recommendation stages before moving to implementation phases.
What outputs does 建模手 provide for model development?
建模手 produces two primary outputs: structured analysis reports and terminology tables. The analysis reports systematically document problem constraints, data requirements, and recommended model approaches. Terminology tables organize key concepts and definitions. These outputs support your model selection and algorithm design phases, providing a clear foundation for implementation.
How does 建模手 help with problem analysis before modeling?
建模手 specializes in the pre-implementation analysis phase. It takes your problem statement and systematically identifies constraints, maps data requirements, and analyzes feasibility. By producing detailed analysis reports and terminology references, 建模手 ensures you have comprehensive understanding and clear model recommendations before beginning actual algorithm design or implementation work.
Let your AI agent find skills like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 56,283 agent skills by what they can do, searchable in plain language.
wish › “Find and install the 建模手 skill for AI agent modeling tasks”
Give your agent the search over MCP, or paste the wish link into any chat. No install? Search from any chat →
Related skills
Math Modeling Skill orchestrates three specialized roles—analyst, programmer, and writer—to guide you from problem interpretation through model development, implementation, and competition-ready documentation. It enforces structured workflows with built-in quality gates and optional peer review at critical stages.
论文手 automates the creation of mathematical modeling competition papers in both Word and LaTeX, ensuring content consistency across formats. It validates official contest rules, manages evidence mapping between claims and results, and enforces quality gates before delivery.
Xlsx handles XLSX file operations including reading, creation, modification and validation with built-in formula recalculation and error detection. The skill preserves templates and named ranges while enforcing strict data validation checks to catch common Excel errors.
This skill builds and validates mathematical modeling LaTeX papers from official or built-in templates, handling project initialization, compilation with XeLaTeX or other engines, and quality checks against contest rules. It can also convert finished LaTeX documents to Word format when needed.
Docx lets you build and modify Word documents programmatically, with native support for LaTeX-to-DOCX conversion, mathematical formulas, three-line tables, tracked changes, and comments. The skill includes templates for competition papers, OOXML validation, and tools to unpack, edit, and repack document structures.
Paper Search queries OpenAlex and AnySearch in parallel to find research papers, then cross-validates results by DOI and title similarity to surface the most relevant matches. Results are ranked by query coverage and relevance, with source attribution preserved for verification.
More skills Webnovel Plan (GPL-3.0) · Plan (GPL-3.0)