Audit or rewrite AGENTS.md so it holds only lasting principles. Run it only when the user asks for it by name; never invoke it on your own.
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。
Generate Ian-style Xiaohei illustrations for articles, posts, blogs, Notion documents, workflows, methods, processes, structures, states, metaphors, and opinions. Use when the user asks for weird, hand-drawn, Xiaohei, article, editorial, body illustrations, illustration ideas, shot lists, title removal, image edits, or image regeneration. By default, all image text and annotations are English, even when the source article is Chinese; only use another language when the user explicitly asks.
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。
Create 16:9 horizontal illustrations for article body sections and blog headers. The goal is not commercial illustration, a slide, or a cute cartoon. Turn the article's key judgment, process, structure, state, or metaphor into a clean, weird, creative, readable-but-not-instructional hand-drawn explanation.
The default visual IP is Xiaohei: a solid-black creature with white dot eyes, thin legs, and a blank expression, seriously doing something absurd but meaningful. Xiaohei must participate in the central action, not stand beside it as decoration.
All visible image text must be English by default. This includes labels, notes, signs, fictional UI text, and tiny annotations. Do not mix in Chinese or other languages unless the user explicitly requests another language.
Keep English labels short, natural, and correctly spelled. Prefer 2–5 words per label.
Do not load every reference unless the task needs it:
references/style-dna.md: visual style, color rules, text rules, and prohibitions.references/xiaohei-ip.md: Xiaohei's appearance, personality, action library, and prohibitions.references/composition-patterns.md: composition types, original-metaphor method, and anti-copying rules.references/prompt-template.md: the single-image generation prompt template.references/qa-checklist.md: post-generation checks and iteration rules.assets/examples/: low-frequency visual calibration only. Do not copy the compositions, objects, or annotations from these examples.Read the user's article, link, Notion page, Markdown file, screenshot, or stated idea. Identify:
Do not illustrate evenly. Prefer cognitive anchors: core judgments, breakpoints, input/output loops, forks, before/after contrasts, reuse paths, handoffs, common traps, and role-state changes.
If the user asks only for analysis or illustration ideas, return a concise shot list first. For each proposed image, include:
Default to 4–8 images. Use 1–3 for a short article. Avoid exceeding 9 unless the article truly needs it.
If the user clearly asks to generate, output, make, or create images, do not stop for confirmation. Generate each image separately. Do not combine multiple illustrations into one image.
Each image explains one core structure. Every prompt must include:
Do not copy prior examples. Examples only calibrate line density, restraint, and how Xiaohei participates. Unless the user explicitly asks to recreate a prior image, invent a fresh metaphor from the current article.
After generation, inspect the image against references/qa-checklist.md. Regenerate or locally edit if any of these occur:
When working in the workspace, save final images under a task-specific folder such as:
assets/<article-slug>-illustrations/
or the folder the user is already using for that article.
Name files in order:
01-topic-name.png
02-topic-name.png
Preserve original generated files. Do not overwrite existing assets unless the user explicitly asks for replacement.
Before generation, keep strategy output concise. After generation, report:
Do not over-explain style theory; let the images speak.
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
Audit or rewrite AGENTS.md so it holds only lasting principles. Run it only when the user asks for it by name; never invoke it on your own.
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。
Audit the choices an implementing agent made, not its diff — a pure decision audit that traces the session's history into a choices ledger, changes no code, and never blocks an unsupervised run. Working code still embeds architecture the user never chose; surface it because future work inherits it. Use when the user wants to review the decisions the AI made on their behalf, before merging or committing AI-implemented work, when integrating a delegated subagent's pass, or when a fix "works" but might be a point fix.
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。
Audit and prioritize performance work through bounded-work and forward-progress checks. Use when asked to find performance issues, investigate freezes/500s/OOMs, review retries or polling for no-progress loops, rank a performance backlog, or implement the next simple performance fixes.
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。
Audit whether tests earn their maintenance cost and which suite owns each contract. Use when pruning redundant tests, investigating implementation coupling or test-only production hooks, reviewing the value of proposed coverage, or auditing an entire subsystem. Use write-tests to implement the resulting test changes.
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。
Run fast, progressive experiments to map tunable parameters and their effects. Use when optimizing code, prompts, configurations, or other artifacts against a goal or benchmark, or when a long research run needs a planned hypothesis queue, focused trials, and durable findings.
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。
Shoot software UI like a film. A sequence of hero shots, each a steep, oblique, extreme close-up of the interface floating in black, with a razor-thin focal plane, a slow motivated camera drift, and UI that acts on its own, hard-cut on the action, ending on one line of copy and a still logo. Use when asked for a launch video, product film, feature trailer, teaser, promo clip, hero shot, or any "cinematic" footage of an app or UI. This skill covers camera, framing, light, and edit. It is stack-agnostic.
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。