基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/jr2804/prompts --skill mcp-sequential-thinking命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | mcp-sequential-thinking |
| description | A detailed tool for dynamic and reflective problem-solving through thoughts that can adapt and evolve |
If MCP server sequential-thinking is available, use this tool to analyze complex problems through a flexible thinking process.
Use sequential-thinking when:
thought: str # Your current thinking step
nextThoughtNeeded: (
bool # True if you need more thinking, even if at what seemed like the end
)
thoughtNumber: int # Current number in sequence (can go beyond initial total if needed)
totalThoughts: int # Current estimate of thoughts needed (can be adjusted up/down)
isRevision: bool # A boolean indicating if this thought revises previous thinking
revisesThought: (
int # If is_revision is true, which thought number is being reconsidered
)
branchFromThought: int # If branching, which thought number is the branching point
branchId: str # Identifier for the current branch (if any)
needsMoreThoughts: bool # If reaching end but realizing more thoughts needed
Thought 1: Analyzing the problem requirements...
Thought 2: Considering possible approaches...
Thought 3: Revising approach from Thought 2 due to X constraint...
Thought 4: Generating solution hypothesis...
Thought 5: Verifying hypothesis...
Create, style, export, and validate publication-quality scientific and technical figures. xy is the preferred default (matplotlib.pyplot-compatible for easy migration); matplotlib/seaborn/plotly also supported. Use when the user asks for a "publication figure", "paper figure", "journal-ready plot", "scientific visualization", "SVG/PDF/TIFF export", "colorblind-safe palette", "multi-panel layout", "error bars / significance markers", or works with figure scripts that import matplotlib, seaborn, plotly, or xy.
Guide for creating, validating, improving, and benchmarking skills. Use when users want to create a skill from scratch, edit or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
Generate comprehensive database schemas with proper relations, migrations, and ORM/ODM models for PostgreSQL, MongoDB, and SQLite. Use when creating database schemas that integrate with FastAPI applications, including SQLAlchemy models for SQL databases, PyMongo/ODMantic models for MongoDB, Alembic migrations, and proper relationship definitions.