一键导入
problem-solving
Broadly and deeply analyze user intent (avoiding XY problems) and evaluate multiple solution approaches (default 5) with scores from 0 to 100.
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。
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Broadly and deeply analyze user intent (avoiding XY problems) and evaluate multiple solution approaches (default 5) with scores from 0 to 100.
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。
基于 SOC 职业分类
Analyze sqlfluff-complexity JSON reports (hotspot digest and threshold tuning). Reuse --output when the file is no older than 5 minutes; otherwise run report. Scan paths and output path are always user-specified.
Guide users through configuring sqlfluff-complexity for a SQLFluff project by sampling reports, choosing a preset, explaining thresholds, per-directory strictness (nested .sqlfluff vs path_overrides), validating config, and recommending gradual CI rollout.
Inspect repository layout with tree and find, compare to AGENTS.md conventions, and fix misplaced or overly flat generated files. Use when auditing folder structure, after scaffolding or bulk file generation, when output looks flat, or when asked where code/tests/docs should live. Supports inspecting the repository root or a specified subdirectory.
Run linters and fix violations using Trunk when available; when Trunk is missing, run the equivalent tools from the dev environment (see .trunk/trunk.yaml and pyproject.toml) so agents still enforce Ruff, Pyright, Pylint, Bandit, and other enabled checks where possible.
Run unit tests and automatically fix code failures, regression bugs, or test mismatches. Use when tests are failing, after implementing new features, or to repair "broken" tests.
Build the project and automatically fix packaging or build errors (for example Hatch failures) and related breakage. Use when the project fails to build, shows "broken" states, or after making significant changes.
| name | problem-solving |
| description | Broadly and deeply analyze user intent (avoiding XY problems) and evaluate multiple solution approaches (default 5) with scores from 0 to 100. |
This skill enables a systematic and thorough evaluation of potential solutions for a given issue. It goes beyond the stated problem to identify the user's true underlying intent, avoiding the "XY Problem" (asking for a solution to an intermediate step rather than the root goal). It ensures that multiple perspectives are considered and that the final recommendation is backed by a structured scoring process.
assets/templates/analysis-report.md template to present your findings.
Input: "We need to migrate our legacy monolith to microservices. Analyze the approaches." Output: A report identifying the intent (e.g., "Improve scalability and deployment speed"). The XY check might note that microservices are a means, not the end. Approaches might include "Modular Monolith" or "Serverless" alongside traditional microservices.
Input: "How do I fix this regex for parsing nested HTML tags in my custom scraper?" Output: A report identifying the Stated Problem (Regex fix) and the Underlying Intent (Extracting data from HTML). The XY check would note that regex is unsuitable for nested HTML. Approaches would include "Use BeautifulSoup/Cheerio", "Use a dedicated HTML parser library", etc., scoring them much higher than the "Fix Regex" approach.