Agent skill

Personal Ip Generator

by Gayaya999 in Gayaya999/personal-ip-generator

Create a consistent personalized IP avatar, character sheet, digital double, sticker set, or expression pack from user-owned portrait photos and a curated catalog of preset visual styles.

MITAuto-check passedAgent Workflows

Install Personal Ip Generator

skills CLI
$ npx skills add Gayaya999/personal-ip-generator --skill personal-ip-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install Gayaya999/personal-ip-generator personal-ip-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
personal-ip-generator
GitHub stars
161
Token cost
~2.3k tokens
SKILL.md length
1,213 words
Files
29 (incl. references, assets)
Skills in repo
1
Repo updated
First seen
Licence
MIT

At a glance

Create a consistent personalized IP avatar, character sheet, digital double, sticker set, or expression pack from user-owned portrait photos and a curated catalog of preset visual styles.

  • Works in 6 steps: Confirm that the images are authorized… → Record line, shape, proportion,… → Ask exactly one question for the user's… → …
  • Codex needs to generate
  • SKILL.md covers Core Rule, Load References, Style Preset Intake and Custom Style Mode, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Personal Ip Generator is an agent skill from Gayaya999/personal-ip-generator. Create a consistent personalized IP avatar, character sheet, digital double, sticker set, or expression pack from user-owned portrait photos and a curated catalog of preset visual styles. Run a strict Plan-Mode-style, one-question-at-a-time wizard before generating. Use when Codex needs to generate or refine a personal IP, 真人卡通形象, 个人头像, 专属角色, 数字分身, 微信表情包, sticker pack, emoji set, select a preset IP style, or derive an original character from a real person's appearance.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 34 other files, including reference files and assets (for example `README.md` and `agents/openai.yaml`).

It sits in Agent Workflows, covering Social media graphics and Planning. The repository describes itself as: A Codex skill for generating consistent personal IP avatars and expression packs with curated style presets. The licence is MIT.

When your agent uses it

  • Codex needs to generate
  • Refine a personal IP
  • Select a preset IP style
  • Derive an original character from a real persons appearance

Example prompts

  • “/personal-ip-generator”

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. Confirm that the images are authorized style references and group the supplied images into one preset.
  2. Record line, shape, proportion, rendering/material, palette, lighting, texture, composition, background, sticker-outline behavior, tags…
  3. Ask exactly one question for the user's Chinese display name, then derive a stable lowercase hyphenated preset ID.
  4. Ask for explicit authorization before copying the reference assets to assets/style-presets//.
  5. Show the proposed preset entry and ask whether it should be active or draft; only active presets appear in user selection.
  6. If an existing preset is materially similar, flag it and let the user choose merge or create-new. Never silently overwrite a preset.

What it can do on your machine

Read from SKILL.md and the folder at commit 73446b1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Personal Ip Generator loads about 2.3k tokens when it runs, and up to ~10k if it reads all its reference files. Until then it costs about 124 tokens; SKILL.md has 1,213 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~124
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~10k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from Gayaya999/personal-ip-generator at commit 73446b1, republished under its MIT licence (© Gayaya999). 1,213 words, ~2,253 tokens.

Download SKILL.mdSave it as .claude/skills/personal-ip-generator/SKILL.md (or your agent's skills folder). This skill also uses 28 other files; get the full folder from GitHub.
name
personal-ip-generator
description
Create a consistent personalized IP avatar, character sheet, digital double, sticker set, or expression pack from user-owned portrait photos and a curated catalog of preset visual styles. Run a strict Plan-Mode-style, one-question-at-a-time wizard before generating. Use when Codex needs to generate or refine a personal IP, 真人卡通形象, 个人头像, 专属角色, 数字分身, 微信表情包, sticker pack, emoji set, select a preset IP style, or derive an original character from a real person's appearance.

个人 IP 生成 Skill

Core Rule

Start with a Plan-Mode-style wizard and ask exactly one material question per assistant turn. Do not generate an image until the user has selected a preset style, the generation profile is complete, and the user has approved the final generation plan.

Treat the selected preset as the style source of truth. Separate identity features from style features before generating. Preserve the person's recognizable anchors while transferring only the preset's approved visual language.

Do not store user portraits inside this skill. Use only images supplied by the user or images the user is authorized to use. Do not infer sensitive attributes such as ethnicity, religion, health, sexuality, or politics from appearance.

Load References

  • Read references/intake-and-style.md whenever reference images are supplied, their roles are unclear, inputs conflict, or a text-only brief is incomplete.
  • Always read references/plan-mode-wizard.md before asking intake questions.
  • Always read references/style-presets.md before presenting or applying preset styles.
  • Read references/prompt-patterns.md before every image-generation call.
  • Read references/qa-and-deliverables.md before generating derivative views or delivering a complete package.

Style Preset Intake

When the user supplies a group of style reference images, treat them as style references unless the user explicitly labels an image as an identity source or an existing IP. Inspect the group before asking the next question and extract one shared style fingerprint; do not copy the depicted person, character, props, text, logo, watermark, or composition.

For a new preset:

  1. Confirm that the images are authorized style references and group the supplied images into one preset.
  2. Record line, shape, proportion, rendering/material, palette, lighting, texture, composition, background, sticker-outline behavior, tags, best uses, and negative constraints.
  3. Ask exactly one question for the user's Chinese display name, then derive a stable lowercase hyphenated preset ID.
  4. Ask for explicit authorization before copying the reference assets to assets/style-presets/<preset-id>/.
  5. Show the proposed preset entry and ask whether it should be active or draft; only active presets appear in user selection.
  6. If an existing preset is materially similar, flag it and let the user choose merge or create-new. Never silently overwrite a preset.

Do not generate an IP image during preset intake. A preset becomes a style authority only after its entry and status are confirmed.

Custom Style Mode

Offer 自定义风格 as a separate style choice alongside active presets. When selected, the user must provide at least one authorized style reference image. Inspect the supplied image or image group, classify it as a style reference, and extract a concrete style fingerprint before asking the next wizard question.

Custom Style Mode is task-scoped by default: use the reference only for the current generation plan and do not copy it into the skill folder or add it to the active catalog. If the user explicitly asks to reuse it later, switch to the Style Preset Intake flow, request authorization to store the assets, assign a stable ID, and ask whether the resulting entry should be active or draft.

Ignore the reference's depicted character, identity, logo, watermark, text, props, and composition unless the user separately requests those elements. The custom reference is a style authority, not an identity source.

Workflow

  1. Identify the IP mode first, with exactly one question.

    • 人物 IP: derive an IP from an authorized person source. On the next turn, collect 1-3 clear portraits or a detailed text description and preserve visible, non-sensitive identity anchors.
    • 代表形象 IP: create an original character that represents a person, team, brand, role, or concept. On the next turn, collect the representative brief; do not imply a real-person likeness without an authorized identity source.
  2. Resolve the style.

    • Present active preset cards with a preview image, Chinese name, 3-5 tags, and best uses, plus 自定义风格 — 上传你的风格参考图.
    • The chosen preset or authorized task-scoped reference is the style authority. Never invent, substitute, or copy a reference character, logo, watermark, text, pose, or composition.
  3. Collect enhanced traits.

    • Ask for 3-5 visible traits to amplify, such as hairstyle, silhouette, outfit direction, occupation cue, personality, accessory, or pose energy.
    • Treat the answer as refinements to the identity/representative brief and selected style; never infer sensitive attributes or reproduce protected branding.
  4. Collect palette direction.

    • Ask the user to choose a compatible palette direction or to use the selected style's default palette.
    • Record dominant, secondary, accent, saturation, temperature, and contrast in the character lock.
  5. Build and show the prompt lock.

    • Include IP mode, identity anchors or representative brief, style fingerprint, enhanced traits, palette, composition, and negative constraints.
    • Ask one approval question before candidate generation. Do not generate images before approval.
  6. Generate one 3x2 preview overview containing exactly six character variants.

    • Create one 3x2 preview overview from the same prompt lock. Preserve the source/representative brief, style, enhanced traits, and palette across all cells; vary only the creative interpretation of silhouette, pose, outfit, accessory emphasis, or expression.
    • Render host-rendered numeric badges on the same overview page after image generation: 1 top-left, 2 top-center, 3 top-right, 4 bottom-left, 5 bottom-center, 6 bottom-right. Do not ask the image model to render the numbers.
    • Ask the user to choose exactly one candidate number. Do not generate final deliverables until a number is selected.
  7. Lock the selected candidate and generate final deliverables.

    • Use the selected preview as the primary identity reference.
    • Generate a centered 1:1 formal avatar and a 3x3 expression-sticker source board. Keep face, hairstyle, silhouette, outfit, palette, material, outline treatment, and accessory placement identical; change only expression and gesture in the board.
    • Compose one 4x3 final delivery board: a formal avatar panel on the left and the 3x3 expression board on the right. Host-render Chinese captions for 正式头像 and the nine expressions: 开心, 大笑, 生气, 委屈, 惊讶, 困惑, 得意, 疲惫, 喜爱.
    • Offer one optional transparent-background cutout export after candidate selection. If the user declines or skips it, deliver the one 4x3 final delivery board with Chinese captions only. If selected, also export nine individual transparent-background expression stickers.
    • Provide the reusable prompt lock and compact character handoff.
  8. Respect the image tool's staged behavior.

    • When the image tool returns one image per call, create the one 3x2 preview overview, formal avatar, expression-board source, and one 4x3 final delivery board across turns without losing the cell mapping or selected reference.
    • After an image-generation call, follow the tool's output rules. On the next turn, continue from the latest accepted candidate without redoing approved work.
Show full SKILL.md (160 more words)Show less

Quality Gates

  • 人物 IP preserves the supplied person's visible anchors; 代表形象 IP remains original and accurately expresses its approved representative brief without implying an unauthorized likeness.
  • The output matches the selected style's visual grammar, not merely its broad genre name, and uses the approved palette direction.
  • One 3x2 preview overview contains exactly six distinct variants with host-rendered numeric badges 1 through 6 on the same page; the underlying generated artwork contains no generated numbering, watermarks, fake logos, or copied characters.
  • One 4x3 final delivery board contains the selected formal avatar and a 3x3 expression board with host-rendered Chinese captions; all panels preserve one locked character identity with no extra limbs, duplicate accessories, or unrelated characters.
  • Transparent-background cutout export is optional and is claimed only after verifying an alpha channel on every individual sticker.
  • Expressions remain readable at small sticker size and differ through face and gesture, not costume redesign.
  • Regenerate only the failed preview or final asset when consistency drifts.

© Gayaya999, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 28 other files (references, assets) in the repository root of Gayaya999/personal-ip-generator.

  • SKILL.md
  • .gitignore
  • LICENSE
  • README.md
  • agents/openai.yaml
  • assets/style-presets/3d-feng/reference-01.png
  • assets/style-presets/3d-feng/reference-02.png
  • assets/style-presets/3d-feng/reference-03.png
  • assets/style-presets/caihui-feng/reference-01.png
  • assets/style-presets/caihui-feng/reference-02.png
  • assets/style-presets/caihui-feng/reference-03.png
  • assets/style-presets/figure-feng/reference-01.png
  • assets/style-presets/figure-feng/reference-02.png
  • assets/style-presets/figure-feng/reference-03.png
  • assets/style-presets/figure-feng/reference-04.png
  • … and 14 more

Open the folder on GitHubat commit 73446b1

Compare with similar skills

Personal Ip Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Personal Ip Generator compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Personal Ip Generator this skillGayaya999/personal-ip-generator161—~2.3kAutomated safety check: PassMIT
Visualize Planyonatangross/orchestkit292—~6.2kAutomated safety check: NotesMIT
Executing Plans Inlineobra/superpowers297k2 repos~5.1kAutomated safety check: PassMIT
Interview Meaddyosmani/agent-skills105k6 repos~3.8kAutomated safety check: PassMIT
OpenSpec Guided OnboardingFission-AI/OpenSpec72k1 repos~4.5kAutomated safety check: PassMIT
Writing Plansgeeksblabla/stateofdev.ma16358 repos~661Automated safety check: PassNone

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Questions about Personal Ip Generator

What does Personal Ip Generator do?

Create a consistent personalized IP avatar, character sheet, digital double, sticker set, or expression pack from user-owned portrait photos and a curated catalog of preset visual styles. Personal Ip Generator is an agent skill from Gayaya999/personal-ip-generator. Create a consistent personalized IP avatar, character sheet, digital double, sticker set, or expression pack from user-owned portrait photos and a curated catalog of preset visual styles.

When should I use Personal Ip Generator?

Personal Ip Generator fits situations like: Codex needs to generate; refine a personal IP; select a preset IP style; derive an original character from a real persons appearance.

How do I install Personal Ip Generator in Claude Code?

Run `npx skills add Gayaya999/personal-ip-generator --skill personal-ip-generator -a claude-code`. Or copy the skill folder (the Gayaya999/personal-ip-generator repository) into .claude/skills/personal-ip-generator in your project. Claude Code loads it when a task matches its description.

How do I install Personal Ip Generator in Codex?

Run `npx skills add Gayaya999/personal-ip-generator --skill personal-ip-generator -a codex`. Or copy the skill folder (the Gayaya999/personal-ip-generator repository) into .agents/skills/personal-ip-generator in your project. Codex loads it when a task matches its description.

Can I use Personal Ip Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add Gayaya999/personal-ip-generator --skill personal-ip-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/personal-ip-generator, .gemini/skills/personal-ip-generator, .github/skills/personal-ip-generator and .opencode/skills/personal-ip-generator in your project.

What does Personal Ip Generator need to run?

SKILL.md names no scripts, command-line tools or credentials: Personal Ip Generator is instructions for the agent only.

Does Personal Ip Generator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Personal Ip Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Personal Ip Generator use?

Personal Ip Generator is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Personal Ip Generator use?

About 2.3k tokens (SKILL.md is roughly 9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 8.1k tokens, read only when the agent opens those files.

What are the alternatives to Personal Ip Generator?

Skills that share tags, products or a category with Personal Ip Generator: Visualize Plan (yonatangross/orchestkit, 292 stars), Executing Plans Inline (obra/superpowers, 297k stars), Interview Me (addyosmani/agent-skills, 105k stars) and OpenSpec Guided Onboarding (Fission-AI/OpenSpec, 72k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Personal Ip Generator?

Gayaya999 (a GitHub user) maintains it in Gayaya999/personal-ip-generator, which has 161 GitHub stars. The repository was last updated on July 15, 2026.

Source: Gayaya999/personal-ip-generator on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.