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SKILL verified MIT Self-run

Avatar Maker

skill-mikefluff-skills-avatar-maker · by Mikefluff

Turn a user photo into N profile-pic / headshot / avatar variants in a consistent style. Identity-preserve focused, defaults to nano-banana-pro. Multi-aspect (square, square-tight, cover 4:5, story 9:16). Use when: 'make me an avatar', 'profile picture from this photo', 'headshot variants', 'LinkedIn profile pic', 'аватарка', 'портрет', 'хедшот'.

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Install

$ agentstack add skill-mikefluff-skills-avatar-maker

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Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access No
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

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Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

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About

Headshot / profile-pic / avatar generator. Input: user photo (REQUIRED) + optional style + optional aspect set. Output: N variant images at chosen aspects, each preserving the original face while applying the style's palette / lighting / composition.

Distinct from flyer-maker / carousel-builder:

  • Single subject focus (the face). No event details, no narrative split, no embedded text.
  • Identity preserve is the PRIMARY constraint — model picker defaults to nano-banana-pro.
  • Multi-variant within an aspect is the common case (give user 3 takes per aspect, pick the best).

This skill does NOT:

  • Generate avatars from text alone — --photo is required (use image-prompt for text-only portrait generation).
  • Render text overlays (name / handle / title) — avatars are visual only. Add text in your design tool if needed.
  • Touch-up / retouch existing photos at the pixel level — the model regenerates the subject in a new style.
  • Generate animal mascots / cartoon avatars without a photo reference — see image-prompt for that.
  • Handle multi-person group photos — single subject only; the model picks one face if given a group.

ROLE

Read user photo + optional style preference → pick a ref-capable identity-preserving model → assemble per-aspect prompts emphasizing identity preserve + style anchor → batch execute → save N variants per aspect → print paths.

PIPELINE

  1. Resolve photo (required):
  • --photo : local file or remote URL.
  • Should be a clean front-facing portrait at ≥800px on the short edge for best results.
  1. Resolve style:
  • --style auto: picks photoreal-friendly styles from carousel library (kinfolk-minimal, photo-editorial-bw, gradient-mesh-modern, dark-academia, …) — avoids illustration / 3D styles where identity gets lost.
  • --style : explicit library entry. Uses the Style anchor (carousel) block.
  • --style-mod "": tweak.
  1. Pick model:
  • --model auto: defaults to nano-banana-pro (best identity preserve).
  • If identity preserve isn't the priority (style transfer first) → flux-2-pro or seedream-5.
  • If embedded brand colors / typography needed → ideogram-3 (rare for avatars).
  • --model : override.
  • ONE model across all aspects + variants.
  1. Build per-aspect prompts:

```

Portrait of the person from the reference image. Preserve identity: face shape, age, ethnicity, hair, distinguishing features. Apply the style's palette, lighting, and composition to the surrounding environment / clothing texture / background — but the face stays recognizably the same person.

Framing: Aspect ratio: Size: ```

  1. Estimate cost + confirmaspects × variants × per-image cost. Default 1 aspect × 3 variants × $0.05 = $0.15. Under budget.
  1. Batch executecommon.runners.batch.run_batch(). Parallelism 3.
  1. Output:

`` ./generated/avatar// square-v1.png ... square-v.png (1080×1080) cover-v1.png ... cover-v.png (1080×1350, if requested) story-v1.png ... story-v.png (1080×1920, if requested) manifest.json style-used.md prompts.md ``

MODES

Required

  • avatar-maker --photo

Style

  • --style auto| — visual style (default: auto, picks photoreal-friendly)
  • --style-mod "" — tweak the anchor

Aspect + variants

  • --aspects square,square-tight,cover,story — comma list (default: square)
  • --variants N — variants per aspect (default 3 — sweet spot for picking the best)
  • --slug — output directory slug (default: derived from photo filename)

Execution

  • --model auto| — image provider (default nano-banana-pro)
  • --execute — actually generate (else returns prompts)
  • --output — custom output dir
  • --parallelism N — concurrent API calls (default 3)
  • --yes — skip cost confirmation
  • --resume — retry failed variants
  • --prompts-only — dry run, save prompts.md, exit
  • --cost-only — print total cost, exit
  • --strict — exit if --model can't handle photo refs

REFERENCES (load on demand)

| File | When to load | |---|---| | [references/model-picker.md](references/model-picker.md) | Step 3 — identity-preserve model comparison, when to pick which | | [references/aspect-presets.md](references/aspect-presets.md) | Step 4 — aspect dimensions, framing conventions per platform (LinkedIn / Twitter / IG / Cover banners) | | [references/troubleshoot.md](references/troubleshoot.md) | When face doesn't look like the original / style overpowers identity / variants look identical |

EXAMPLES

See [examples/before-after.md](examples/before-after.md) — 3 calibration runs: founder headshot for LinkedIn (kinfolk-minimal, 3 variants), photo-editorial B&W portrait set, multi-aspect avatar set for someone setting up new social accounts (square + cover-banner + story).

CONSTRAINTS

  • Identity preserve is paramount. Nano Banana Pro is the safest pick. If --model is overridden and identity gets lost, the troubleshoot reference covers fixes.
  • Use a clean source photo. ≥800px on the short edge. Front-facing or 3/4. Even lighting. Avoid heavy shadow / backlight / partial occlusion.
  • No mid-image text. Avatars are visual-only. Don't add --title or similar.
  • Default 3 variants per aspect. Models produce stochastic variation — 3 takes lets the user pick the best. Past 5, diminishing returns.
  • One model across the run. Mixing providers breaks consistency.
  • One style across the run. Same anchor across all aspects + variants.
  • Photoreal-friendly styles win. Carousel library has illustration / 3D / abstract styles (flat-vector-illustration, low-poly-3d, paper-cutout-craft) — these LOSE identity. --style auto filters them out. If explicitly chosen, the result will look more like "a person in that style" than "this specific person".
  • Cost confirm ONCE per batch. Sum across aspects × variants.
  • Output slug derived from photo filename by default. Override via --slug or --output.
  • Manifest updates after every variant. --resume retries failed only.
  • Photo can be local or URL. Provider routes accordingly.
  • Never print API keys. Mask in errors.
  • Output dir is ./generated/avatar// by default.

INVOCATION HINTS

When the user says any of:

  • "make me an avatar / profile pic from this photo"
  • "headshot variants", "portrait variants"
  • "LinkedIn profile picture", "Twitter profile pic", "Instagram avatar"
  • "professional headshot", "business portrait"
  • "branded avatar set" (variants in different aspects for cross-platform consistency)
  • "сделай аватарку / портрет / хедшот"
  • "профиль для LinkedIn / Twitter / IG"
  • "аватарка с моей фоткой"

Defaults: --aspects square --variants 3 --style auto --model nano-banana-pro. Without --execute, returns prompts; with --execute, generates.

If the user mentions LinkedIn → emphasize --aspects square (LinkedIn profile is 1:1 + a 4:1 cover-banner area; the cover aspect is closer to LinkedIn cover banner).

If the user mentions cross-platform: --aspects square,square-tight,cover gives them 1:1 for most + a tighter crop for small profile thumbs + a cover banner.

This skill is distinct from:

  • flyer-maker — that's events with embedded text; this is identity-preserved portraits
  • image-prompt — that's any image; this is specifically photo-input → variant portraits
  • carousel-builder — that's narrative slides; this is variants of one subject

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.