القائمة
Refactor Python code to improve quality while keeping functionality intact. Use when cleaning up complexity, removing duplication, or tightening structure.
التثبيت باستخدام Codex أو Claude انسخ هذا Prompt والصقه في Codex أو Claude أو مساعد آخر ليراجع صفحة Skill ويثبّتها لك.
استنادا إلى تصنيف SOC المهني
ALWAYS use this skill whenever you would otherwise ask the user a question in free-form chat -- for clarifications, confirmations (especially destructive actions), missing parameters, multiple-choice decisions, or structured form input. Elicitations are routed through the Unique AI Platform UI via `unique-cli elicit create` + `elicit wait` (or `elicit ask` outside an agent harness) so the user gets a proper structured prompt and you get a structured answer back. Do NOT ask the user in plain chat when you can use this skill instead.
Read Agentic Table (magic table / due-diligence) sheets through the unique-cli agentic-table command. Use when the user or task involves inspecting an Agentic Table: a sheet's state and metadata, a specific cell's value or lock state, a cell's edit/answer history, or the sheet's generated export artifacts (reports, question exports). These are read-only (Tier 0) commands — they never modify the sheet and never require confirmation. Access to each sheet is enforced by the platform; a denial is reported as `agentic-table: permission denied`.
Call MCP (Model Context Protocol) server tools on the Unique AI Platform using the unique-cli mcp command. Use when the user asks to invoke, call, or execute an MCP tool, or when they need to send a JSON payload to an MCP server through the CLI. The JSON payload is forwarded 1:1 to the platform's MCP call-tool API.
Invoke connected Unique spaces/subagents through the unique-cli subagent command. Use when the workspace exposes connected-space tools and you need to delegate a question or task to one of those configured assistants.
Search the Unique AI Platform knowledge base using the unique-cli search command, with automatic per-turn citation tracking so cited facts render as clickable reference chips and `<sup>N</sup>` footnotes on the Unique platform. Use whenever the user asks to find, search, or query documents or content on Unique, including filtering by folder or metadata. Also covers `unique-cli read <cont_id>` for reading the full indexed text of a document when its content ID is already known. NOTE: This search uses combined vector + full-text indexing. Excel (.xlsx/.xls), CSV (.csv), and image files are NOT full-text indexed, so they will not appear in search results. To locate these file types, use the unique-cli-file-management skill instead (browse folders with `unique-cli ls` to find them by name).
Search the documents uploaded for the CURRENT task/row (e.g. an Agentic Table row's attached files) via the `unique-cli uploaded-search "<query>"` command, with the same per-turn citation tracking as `unique-cli search` so cited facts render as `<sup>N</sup>` footnotes and clickable reference chips on the Unique platform. ALWAYS use this skill when the user refers to documents they uploaded/attached to this task, or when you need facts from the task's own attached files. These uploaded files are scoped to the chat, NOT to a knowledge-base folder, so they will NEVER appear in `unique-cli search` results no matter the folder or metadata filters. Use `unique-cli search` for the knowledge base and this command for the task's uploaded documents; the two are complementary and citation numbering is shared across them within a turn.
| name | refactor-code |
| description | Refactor Python code to improve quality while keeping functionality intact. Use when cleaning up complexity, removing duplication, or tightening structure. |
| license | MIT |
| compatibility | claude cursor opencode |
| metadata | {"version":"1.0.0","languages":"python","audience":"developers","workflow":"refactor","since":"2026-02-25"} |
Improve readability, maintainability, and testability without changing behavior.
Code quality improvements
dict/tuple blobs with Pydantic BaseModels where appropriateReduce complexity
Enhance maintainability
Optimize but stay Pythonic