Write and optimize prompts for AI-generated outcomes across text and image models. Use when crafting prompts for LLMs (Claude, GPT, Gemini), image generators (Midjourney, DALL-E, Stable Diffusion, Imagen, Flux), or video generators (Veo, Runway). Covers prompt structure, style keywords, negative prompts, chain-of-thought, few-shot examples, iterative refinement, and domain-specific patterns for marketing, code, and creative writing.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Craft effective prompts for AI text and image generation models.
[Role] You are a {expert type} specializing in {domain}.
[Context] {Background information and constraints}
[Task] {Specific action to perform}
[Format] {Output structure - JSON, markdown, list, etc.}
[Examples] {1-3 few-shot examples if needed}
[Subject] {main subject with details}
[Style] {artistic style, medium, artist reference}
[Composition] {framing, angle, lighting}
[Quality] {resolution modifiers, rendering quality}
[Negative] {what to avoid - only if supported}
Example: Portrait of a cyberpunk hacker, neon lighting, cinematic composition, detailed face, 8k, artstation quality --ar 16:9 --style raw
Load for detailed guidance:
| Topic | File | Description |
|---|---|---|
| LLM | references/llm-prompting.md | System prompts, few-shot, CoT, output formatting |
| Image | references/image-prompting.md | Style keywords, model syntax, negative prompts |
| Nano Banana | references/nano-banana.md | Gemini image prompting, narrative style, multi-image input |
| Advanced | references/advanced-techniques.md | Meta-prompting, chaining, A/B testing |
| Domain Index | references/domain-patterns.md | Universal pattern, links to domain files |
| Marketing | references/domain-marketing.md | Headlines, product copy, emails, ads |
| Code | references/domain-code.md | Functions, review, refactoring, debugging |
| Writing | references/domain-writing.md | Stories, characters, dialogue, editing |
| Data | references/domain-data.md | Extraction, analysis, comparison |
| Model | Key Syntax |
|---|---|
| Midjourney | --ar, --style, --chaos, --weird, --v 6.1 |
| DALL-E 3 | Natural language, no parameters, HD quality option |
| Stable Diffusion | Weighted tokens (word:1.2), LoRA, negative prompt |
| Flux | Natural prompts, style mixing, --guidance |
| Imagen/Veo | Descriptive text, aspect ratio, style references |
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
[00] TnR ABSOLUTE RIGOR — Systemic Verification Doctrine. Forced cognitive exertion for high-stakes investigations. Mandates absolute deconstruction, mathematical proof chains, and ≥95% derived certainty. Zero-tolerance for heuristics or sentiment-based reasoning. Shortcuts are defined as intentional hallucinations.
日本語の概要は準備中です。原文の説明を表示しています。
Configures 2-Agent workflow between PM and implementation roles. Use when user mentions 2-Agent, 2エージェント, PM連携設定, Cursor設定, Cursor連携, 2-agent運用. Do NOT load for: 単独運用, ワークフロー実行, ハンドオフ処理.
Appends relevant hashtags to journal entries based on content analysis. Intended for LLM execution.
日本語の概要は準備中です。原文の説明を表示しています。
Add a new AI coding agent to Agent Sandbox. Creates all required files (Dockerfile, templates, CI, docs) and wires the agent into the CLI, proxy, and build system.
日本語の概要は準備中です。原文の説明を表示しています。
Add a new property to the AI agents database. Use when the user wants to add, create, or introduce a new column, property, field, or feature to track across all agents in the comparison matrix. Handles all four required steps - database updates, groups.json, table display, and GitHub issue templates.
日本語の概要は準備中です。原文の説明を表示しています。
Add new Agent templates to the meta-agent-skills framework.
日本語の概要は準備中です。原文の説明を表示しています。