DeepSeek Whale-chan skill
Two skills for Codex and Claude Code draw fan illustrations and comics of Whale-chan with her look kept consistent
- 543 ★ on the repository
- Last commit
- MIT
Extended access
Why this level
- Runs local scripts and ImageMagick and writes image files and a gallery into run folders
- Calls paid image generation channels from OpenAI, Gemini or Ark with keys from the environment and spends their limits
Install
- Works in
In your terminal, with SkillFoxx CLI
npx skillfoxx add skills/deepseek-whale-chanDetects the agents on your machine, shows the access level and pins the version.
Other ways to install
Access and checks
How we reviewExtended accessThe tool runs code or makes network calls and only reads external data.
- Runs local scripts and ImageMagick and writes image files and a gallery into run folders
- Calls paid image generation channels from OpenAI, Gemini or Ark with keys from the environment and spends their limits
This is third-party code. Review the repository files before installing.
What it does
The repository is a kit for consistent illustrations of Whale-chan, a fan-made whale-girl character from the DeepSeek community. The whalechan-image-character skill proposes illustration directions, you pick them at the first gate, then separately confirm quantity, visual settings and candidate budget, and only then does the skill generate verified PNGs. whalechan-image-comic comes up with 2N short ideas, an independent subagent picks N, and one comic is drawn per chosen idea. N defaults to five. The look is locked by reference images: hair gradient, whale-fin ears, cowlick, tail and a maid uniform. Proportions come in five forms from 4.0 heads to 2.1 heads, and skeleton placement is verified by measurement. A character mindset engine picks the source's comedy move, reversal, exposure, escalation or recognition, and keeps the humor in the character's lines and reactions. Images are made with Codex ImageGen by default, and other agents call it through codex exec. Fallback channels are OpenAI Images, Gemini and Volcengine Ark through keys in environment variables. Output is assembled into an offline gallery.
Who it is for. Fan content and sticker creators working in Codex, Claude Code or Gemini who want series of images with the same character.
Good fit when
- You need an 8:3 promotional banner or poster with the character in a consistent look
- You want a four-panel comic from an error screenshot or a model's reasoning, retold as the character's joke
- You need stickers in the super-deformed form at 2.1 heads
- You need a fixed set of variants: Whale-chan in five forms for a series of posts
Not a fit when
- You need official DeepSeek artwork: the project is unofficial and unaffiliated with the company
- You need another character or your own style: Whale-chan's look and proportions are locked
- You need commercial materials without a rights check: the authors separately note character authorship and trademarks
Example request
Using $whalechan-image-character, make an 8:3 banner of Whale-chan eating rice by a server rack in the semi-chibi formLimitations
- The project is unofficial and unaffiliated with DeepSeek, and DeepSeek and other brand names belong to their owners. The character was created by the community, and the README covers rights to it separately.
- ImageMagick is needed for validation and panel composition.
- Codex ImageGen makes the images, so other agents need an installed and logged-in Codex CLI. Fallback channels need OpenAI, Gemini or Volcengine Ark keys.
- Generation runs in several confirmed steps with up to 10 workers and a candidate budget, so a series takes time and spends limits.
How to disable. Delete the whalechan-image-character and whalechan-image-comic folders from the agent's skills directory, for example ~/.claude/skills or ~/.codex/skills, and restart the session. Created images live in run folders and are deleted by hand. Remove API keys from your shell profile environment variables.
FAQ
What is Whale-chan?
A fan-made character from the DeepSeek community: a girl with whale-fin ears and a whale tail in a maid uniform who believes white rice is the main currency of computing. The project is community-made and not officially affiliated with DeepSeek.
How do I install the Whale-chan skills in Claude Code?
Clone the repository, install ImageMagick and run cp -R skills/* ~/.claude/skills/. For Codex the directory is ~/.codex/skills. After restarting the session the skills are available as whalechan-image-character and whalechan-image-comic.
Do I need API keys to generate images?
Not for the main path: Codex ImageGen needs no external keys, and other agents call it through a logged-in Codex CLI with codex exec. OpenAI, Gemini or Volcengine Ark keys are needed only for the fallback channels.
Which forms does the character have?
Five: standard (4.0 heads), compact (3.3), semi-chibi (2.8, the default), chibi (2.5) and super-deformed (2.1). Allowed proportion ranges are checked by measurement.
How many comics does the skill make per run?
Five by default: the skill comes up with 2N ideas, an independent subagent picks N, and one comic is drawn for each. The number can change, and the batch ceiling is 10 workers.
Discussion
No questions or reviews yet.
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README in short
The README opens with a disclaimer about its unofficial status, then describes the character, five forms with proportion tolerances and example galleries. A table of the two skills, installation into Codex, Gemini and Claude Code, key setup and quickstart scenarios follow.
README badge
Original SKILL.md
--- name: whalechan-image-character description: Propose DeepSeek Whale-chan character illustrations, let the user select directions, then separately confirm quantities, visual settings and candidate budget before generating verified PNGs. Use for character portraits and themed illustrations with consistent identity and customizable visuals; default to one image per selected proposal. --- # Whale-chan Image Character Create verified Whale-chan PNGs. Preserve Whale-chan's permanent identity while resolving every visual dimension independently from the user's request, typed reference images, and canonical defaults. A custom value changes only its own field. Workflow: propose → **Gate 1: select directions** → **Gate 2: confirm scope and begin** → expand, validate and freeze → generate, review and deliver. Selection alone is not permission to generate. ## Load guidance as needed - Read `references/proposal-selection.md` before presenting either gate or interpreting replies. - Read `references/assignment-schema.md` whenever normalizing, confirming, or freezing a request. - Read `references/character-spec.md` before building prompts or deciding whether a requested customization preserves Whale-chan identity. - Read `references/form-profiles.md` when resolving or measuring proportions. The five bundled forms are recommended presets, not the only allowed ratios. - Read `references/reference-index.md` when selecting bundled or user-supplied references. - Read `references/provider-routing.md` before any provider call or parallel run. - Read `references/qa-rubric.md` before reviewing or promoting a candidate. - Read `references/gallery.md` before exporting the completed task's preview gallery. - Treat `references/reference-catalog.json` as the machine-readable authority for bundled paths, hashes, preset ratios, and preset acceptance ranges. ## Choose the language Read `references/language-policy.md` before planning. Resolve one task `language`: explicit user instruction → meaningful current-session expression → newest meaningful local session within 24 hours → ask when uncertain. Use `scripts/detect-language.py` for historical evidence, not as an automatic verdict; recent sessions take precedence over aggregate counts. Save the normalized BCP-47 tag, actual resolution evidence and any explicit scoped overrides. Use it for communication, image lettering, HTML UI, drawing prompts and visible run/image titles. Preserve exact locked wording and necessary technical tokens. Keep internal IDs and filenames in English. Propagate the saved language to workers and resume from it; never redetect during execution. Prepare required plan/prompt locale sections before confirmation; use the offline gallery language selector for UI only. Keep generated content in its recorded language. See the language policy for custom dictionaries, display titles, scoped overrides and legacy compatibility. ## Resolve the request Resolve the request field by field while planning; build the complete schema v7 assignment only after Gate 2. Use the user's explicit instructions first, then references only for their declared roles, then canonical defaults for unresolved fields. Do not let a reference silently control unrelated dimensions. Defaults: - Five directions for an open theme; one image per selected proposal. A precisely specified scene uses direct proposals without inventing five alternatives. - `semi-chibi`; canonical style; canonical maid outfit. - Warm ivory-beige solid background `#F5EADD`; transparency off. - No visible text. When text is requested without a language, use the session language (see [Choose the language](#choose-the-language)); do not translate or invent wording without confirmation. - Full-body centered composition, `1:1`, PNG, provider-native resolution, automatic sub-agent execution (up to 10 workers, resolved from actual capacity before Gate 2). Prefer 1024×1024 when the selected provider exposes a compatible size control, but do not treat 1024×1024 as a default acceptance requirement. The user may explicitly request any style, action, outfit, solid/custom/transparent background, exact multilingual text, measurable head ratio greater than 1.0, positive-integer aspect ratio, or exact positive pixel resolution. If the user gives only width and height, derive the aspect ratio; if both are given, require them to agree. Keep extreme but measurable ratios possible; disclose that ratios outside the five presets have no bundled proportion reference and may be harder to satisfy. Provider safety and technical limits still apply.