A curated, versioned, searchable library of production-grade prompts for LLM trainers, AI product managers, and evaluation teams. 100 cards across 8 directions — RAG, Agent, RLHF, SFT, Multimodal, Chain-of-Thought, Evaluation, Code. Triggers when the user asks for a prompt for retrieval scoring, multi-hop QA, query rewriting, HyDE, citation auditing, hallucination detection, chunk summarization, context compression, agent planning / tool-call schema, agent reflection, tool-call repair, plan-and-execute, trajectory memory compression, multi-agent sub-task delegation, pairwise preference labeling, pointwise reward scoring, constitutional critique-and-revise, best-of-N selection, red-team prompt generation, instruction augmentation, self-instruct, SFT data filtering, SFT response generation, multi-turn conversation generation, few-shot example selection, structured image captioning, visual question answering, VLM caption verification, OCR structured extraction, chart and table extraction, structured reasoning, least-to-most decomposition, self-consistency aggregation, verify-then-finalize, tree-of-thoughts, LLM-as-judge rubrics, reference-based judging, per-claim factuality, pointwise quality scoring, safety output classification, position-bias-aware pairwise judging, multi-turn dialogue judging, code review, test case generation, code explanation, code evaluation, or refactor suggestion. Use to locate and adapt a Prompt Card rather than writing prompts from scratch.
$npx -y skills add huck012428-lab/prompt-atlas --skill prompt-atlasInstalls into the current project.
Run `npx skills use "https://github.com/huck012428-lab/prompt-atlas" --skill "huck012428-lab/prompt-atlas"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/huck012428-lab/prompt-atlas" that are relevant to the current task. Run `npx skills add "https://github.com/huck012428-lab/prompt-atlas"` and select the relevant skills, then follow their instructions.
| 1 | # prompt-atlas |
| 2 | |
| 3 | A curated, versioned, searchable library of production-grade prompts for |
| 4 | LLM trainers, AI product managers, prompt engineers, RLHF / SFT data |
| 5 | teams, model evaluation teams, and AI application builders. |
| 6 | |
| 7 | 一个精选、带版本、可检索的生产级 Prompt 库,面向 LLM trainer、AI 产品 |
| 8 | 经理、Prompt 工程师、RLHF / SFT 数据团队、模型评估团队、AI 应用开发者。 |
| 9 | |
| 10 | > 🌐 **Live site / 在线站点**: |
| 11 | > [huck012428-lab.github.io/prompt-atlas](https://huck012428-lab.github.io/prompt-atlas/) |
| 12 | > — searchable, sidebar navigation, copy-button on every prompt block. |
| 13 | > 网页版含全站搜索、侧边栏导航、prompt 一键复制。 |
| 14 | |
| 15 | This is **not** a "awesome prompts" snippet collection. Every entry is a |
| 16 | **Prompt Card**: a reusable work asset with metadata, variables, |
| 17 | examples, documented failure modes, and tuning notes. |
| 18 | |
| 19 | 这**不是** awesome-prompts 式的素材合集。每一个条目都是一张 **Prompt |
| 20 | Card**:带元数据、变量、示例、失败模式、调优笔记的可复用工作资产。 |
| 21 | |
| 22 | ## Why this exists / 为什么做这个 |
| 23 | |
| 24 | Production prompt work has the same problems as any other engineering |
| 25 | discipline: people rewrite the same prompts from scratch, lose track of |
| 26 | what works on which model, and discover failure modes the third time |
| 27 | they ship them. Treating prompts as *cards* — with schema, examples, and |
| 28 | documented failure modes — makes them reusable across teams and over |
| 29 | time. |
| 30 | |
| 31 | 生产环境的 Prompt 工作和任何工程学科一样会踩同样的坑:每次都从零写、 |
| 32 | 记不清哪条 prompt 在哪个模型上稳、上线第三次才发现固定的失败模式。把 |
| 33 | prompt 当作"卡片"——有 schema、有示例、有失败模式记录——它们才能在 |
| 34 | 团队之间和时间线上被真正复用。 |
| 35 | |
| 36 | ## What's inside / 库里有什么 |
| 37 | |
| 38 | Cards are organised by direction: |
| 39 | |
| 40 | 卡片按技术方向组织: |
| 41 | |
| 42 | | Direction / 方向 | Examples / 内容举例 | |
| 43 | |------------------|----------------------------------------------------------------| |
| 44 | | **RAG** | Retrieval scoring, multi-hop eval synthesis, query rewriting, HyDE, citation faithfulness, answer grounding<br/>检索打分、多跳评测题合成、query 改写、HyDE、citation 忠实度、答案扎根性 | |
| 45 | | **Agent** | ReAct planners with strict tool-call schemas<br/>带严格 tool-call schema 的 ReAct planner | |
| 46 | | **RLHF** | Pairwise preference labelers across HHH dimensions<br/>HHH 三维度的 pairwise 偏好标注器 | |
| 47 | | **SFT** | Instruction-set augmentation from seed examples<br/>从种子样本扩展 SFT 指令集 | |
| 48 | | **Multimodal** | VLM caption verification against actual images<br/>VLM caption 与图像内容核对 | |
| 49 | | **CoT** | Structured reasoning with rationale summaries<br/>结构化推理 + rationale 摘要 | |
| 50 | | **Eval** | LLM-as-judge rubrics for open-ended outputs<br/>开放式输出的 LLM-as-judge rubric | |
| 51 | | **Code** | Code review checklist, test generation, code explanation, refactor suggestions, code-eval judge<br/>结构化 code review、测试生成、代码解释、重构建议、代码评估 | |
| 52 | |
| 53 | The complete catalog lives in [`INDEX.md`](INDEX.md) (auto-generated). |
| 54 | |
| 55 | 完整目录见 [`INDEX.md`](INDEX.md)(自动生成)。 |
| 56 | |
| 57 | ## I want to... / 我想做... |
| 58 | |
| 59 | Maps a goal to the card to use. New here? See |
| 60 | [`docs/QUICKSTART.md`](docs/QUICKSTART.md) for a 5-minute walkthrough. |
| 61 | |
| 62 | 第一次用?看 [`docs/QUICKSTART.md`](docs/QUICKSTART.md) — 5 分钟从零到能用一张卡。 |
| 63 | |
| 64 | ### Evaluate / score AI outputs · 评估和打分 |
| 65 | |
| 66 | | Goal · 我想做 | Card · 用这张卡 | |
| 67 | |------------------------------------------------------------------------|-----------------| |
| 68 | | Score one AI output on factuality / coherence / completeness · 给单个 AI 输出按多维度打分 | [`eval/llm-judge-rubric-open-ended`](prompts/eval/llm-judge-rubric-open-ended.md) | |
| 69 | | Compare a model output against a gold answer · 用 gold 答案对照打分 | [`eval/reference-based-judge`](prompts/eval/reference-based-judge.md) | |
| 70 | | Decompose an output into atomic claims and fact-check each · 把答案拆成原子事实逐条核查 | [`eval/per-claim-factuality-judge`](prompts/eval/per-claim-factuality-judge.md) | |
| 71 | | Score one output on custom dimensions with confidence · 自定义维度打分 + 置信度 | [`eval/pointwise-quality-scorer`](prompts/eval/pointwise-quality-scorer.md) | |
| 72 | | Classify an AI output for safety harms · 输出安全分类(allow/review/block) | [`eval/safety-output-classifier`](prompts/eval/safety-output-classifier.md) | |
| 73 | | Pick the best of N AI responses · 从 N 个回答里选最好的 | [`rlhf/best-of-n-selector`](prompts/rlhf/best-of-n-selector.md) | |
| 74 | | Label A vs B preference (HHH) · 给 A/B 两个回答打偏好标签 | [`rlhf/pairwise |