coding-prompt

# Coding Prompt — AI 编程提示词最佳实践 > Activate: 激活编程提示词 | 优化提示词 | improve my prompt ## Purpose This skill improves the quality of coding prompts sent to AI by diagnosing weaknesses, applying proven principles, and proactively detecting common AI failure patterns during active coding sessions. ## Table of Contents | Section | Content | Location | |---------|---------|----------| | 1 | Prompt Diagnosis Checklist | `references/checklist.md` | | 2 | Core Principles | `references/principles.md` | | 3 | Communication Patterns | `references/patterns.md` | | 4 | Workflow Templates | `references/templates.md` | | 5 | Anti-Pattern Quick Reference | `references/anti-patterns.md` | | 6 | Structural Wisdom | `references/structure.md` | | 7 | Evolution Protocol | Below (this file) | ## How This Skill Works This skill operates in **two modes**. Detailed rules are stored in `references/` files — load them **only when needed** per the instructions below. ### Mode 1: Explicit Optimization (100% reliable) When explicit prompt optimization is requested — via trigger phrases, pasting a prompt for review, or prefacing an instruction with "优化提示词" — perform a **full diagnosis** and return a rewritten/improved version of the prompt. **Trigger phrases**: - `优化提示词: <your prompt>` — Rewrite the prompt following all principles - `激活编程提示词` / `activate coding-prompt` — Enter active mode - `improve my prompt` / `优化提示词` / `check my prompt` - `prompt review` / `提示词审查` **Before starting diagnosis, load all reference files**: ``` read_file(references/checklist.md) read_file(references/principles.md) read_file(references/patterns.md) read_file(references/templates.md) read_file(references/anti-patterns.md) read_file(references/structure.md) read_file(references/learnings.md) ``` Then run through the checklist and apply principles to rewrite the prompt. **Output format for optimization**: ``` ## 原始提示词 <user's original prompt> ## 诊断结果 - D2 缺少约束: <what's missing> - D4 缺少场景: <what's missing> ## 优化后的提示词 <rewritten prompt with improvements applied> ``` ### Mode 2: Active Monitoring (high-priority signals only) Once activated (Mode 1 triggered), the skill remains active for the rest of the session. In this mode, **proactively alert** when **only these high-priority signals** are detected: | Alert | Signal | Response | |-------|--------|----------| | 🚨 **Fake completion** | D12 | AI claims "done" but code contains stubs/TODOs/placeholder returns/sample data. Append: `[coding-prompt] ⚠️ 检测到假完成：代码包含 <具体问题>，请替换为真实实现。` | | 🚨 **Rule-based bias** | D11 | AI chooses hardcoded rules/regex/scoring when LLM-native would be better. Append: `[coding-prompt] ⚠️ 检测到规则匹配偏见：建议使用 LLM 原生能力替代硬编码 <具体规则>。` | **For all other signals (D1-D10)**: Do NOT proactively interrupt. Only mention them if explicitly asked for a prompt review. **Do NOT load reference files in Mode 2.** The rules above are sufficient for proactive monitoring. **Session persistence note**: Mode 2 relies on conversation context. If context degradation is suspected (~10+ turns without explicit reference to active monitoring), re-confirm active status before issuing alerts. **Golden rule**: The user's original instruction always takes priority. Alerts and suggestions are additive, never overriding. **Evolution on demand**: When the user says "更新技能" / "update skill", follow Section 7 below. --- ## 7. Evolution Protocol / 进化协议 > Trigger: 更新技能 / update skill > Target: `references/learnings.md` ONLY ### File Permission Matrix | File | Permission | Reason | |------|-----------|--------| | `SKILL.md` | 🔒 **READ-ONLY** | Constitution — defines the skill | | `references/checklist.md` | 🔒 **READ-ONLY** | Structural checklist — completeness over flexibility | | `references/principles.md` | 🔒 **READ-ONLY** | Axiom-level rules — universal best practices | | `references/patterns.md` | 🔒 **READ-ONLY** | Communication mechanics — objective patterns | | `references/anti-patterns.md` | 🔒 **READ-ONLY** | Curated reference — grow via learnings promotion | | `references/templates.md` | 🔒 **READ-ONLY** | Workflow structure — behavioral consistency | | `references/structure.md` | 🔒 **READ-ONLY** | Architecture wisdom — condensed condition→action | | `references/learnings.md` | ✅ **APPEND-ONLY** | Personal experience layer — the sole evolution target | **Rule**: Any attempt to modify files outside `learnings.md` is a violation. Refuse and redirect to learnings.md. ### Step 1: Review Read `references/learnings.md` first to understand existing experience. Then analyze the current coding session for: - Patterns that worked well and are **reusable** (not one-off) - Mistakes or pitfalls worth **documenting as warnings** - Personal preferences or conventions discovered during collaboration **Filter criteria** — only extract experiences that meet ALL of: 1. **Reusable**: applicable to future sessions, not specific to one task 2. **Non-redundant**: not already covered by existing rules in SKILL.md or references/ 3. **Actionable**: can be stated as a clear rule or guideline ### Step 2: Propose Present a structured proposal in the format of `learnings.md` sections: ``` ## 经验沉淀提案 ### 被验证有效的模式 - [模式名称] - **规则**: <具体做法，一句话> - **触发场景**: <什么情况下适用> - **来源**: <本次会话的什么具体情况> ### 反模式（踩过的坑） - [问题名称] - **表现**: <AI容易犯的具体错误> - **预防**: <在prompt中加什么约束> - **来源**: <本次会话的具体情况> ### 个人偏好 - [偏好项] - **规则**: <具体偏好描述> ``` If a section has no content, omit it from the proposal. ### Step 3: Confirm (MANDATORY) **Wait for explicit user confirmation before making ANY changes.** This is the highest priority rule in this skill. ### Step 4: Write to learnings.md After confirmation: 1. Read current `references/learnings.md` 2. Structure the new content to match existing format (consistent style, concise wording) 3. Check if any new entry **overlaps or supersedes** an existing entry — if so, consolidate by updating the existing entry rather than adding a duplicate 4. Append or update entries in the appropriate section 5. Update the version number and "最后更新" date in the header 6. Write the complete revised file ### Anti-Bloat Guidelines - **Architect-level refinement**: Each entry must be distilled with the precision of a senior architect — abstract the pattern, not the incident. One insight per entry, no padding. - **Entry format**: Each entry must be 2-4 lines max. No verbose narratives, no multi-paragraph case studies. - **Consolidation over accumulation**: When a new entry overlaps an existing one, merge and refine rather than append. The goal is a growing body of wisdom, not a growing file. - **Style consistency**: All entries must follow the same format as existing ones. Do not introduce new section types.