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/upscaler

Image upscaling utility — image in, upscaled image out (2× / 4× / 8×). Wraps Replicate upscalers (Real-ESRGAN default; GFPGAN for faces, SwinIR, clarity-upscaler). Optional --face-enhance for portrait restoration. Use when: 'upscale', 'enhance resolution', 'sharpen low-res

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skills
2645 skills2 commands1 hook

Claude Code

$ npx -y skills add Mikefluff/skills --skill upscaler --agent claude-code

SKILL.md

upscaler.SKILL.md
name: upscaler
description: "Image upscaling utility — image in, upscaled image out (2× / 4× / 8×). Wraps Replicate upscalers (Real-ESRGAN default; GFPGAN for faces, SwinIR, clarity-upscaler). Optional --face-enhance for portrait restoration. Use when: 'upscale', 'enhance resolution', 'sharpen low-res image', 'make this bigger', 'улучши разрешение', 'увеличь фотку', 'апскейл'."

license: MIT
allowed-tools:
  - Read
  - Write
  - Edit
  - Bash
  - Grep
  - Glob

<objective> Image upscaling utility. Single input image → output upscaled by 2× / 4× / 8× factor. Sharper, higher resolution, with AI-based detail interpolation (vs simple bilinear / bicubic).

This skill does NOT:

  • Generate new content — it ENHANCES existing pixels via super-resolution models
  • Magic-restore an image from junk-tier (16×16 thumbnail to 4K HD) — input quality matters; garbage in, garbage out
  • Handle video — one frame at a time only
  • Vectorize — output remains raster PNG
  • Remove background (chain with `bg-remover`)
  • Fix major artifacts (deep blur, motion blur, JPEG mosquito noise at extreme levels) — works best on mildly low-res / soft images

</objective>

ROLE

Read input image → call a Replicate-hosted upscaler → save the upscaled output at the requested scale factor.

PIPELINE

1. **Resolve input**:

  • `--image <path-or-url>` (required)

2. **Pick provider**:

  • Default: `nightmareai/real-esrgan` (popular general-purpose, ~$0.005/image at 4×)
  • Alternatives via `--replicate-model <id>`:
  • `nightmareai/real-esrgan` — default; best general
  • `tencentarc/gfpgan` — face-focused (best for portraits)
  • `jingyunliang/swinir` — alternative general
  • `philz1337x/clarity-upscaler` — high-fidelity preservation, slower
  • Other Replicate upscalers: pass via `--replicate-model <slug>`

3. **Scale**: `--scale 2|4|8` (default 4).

4. **Face enhance** (optional): `--face-enhance` enables face restoration (Real-ESRGAN supports GFPGAN-style face restoration as a flag).

5. **Execute** via the Replicate router (REPLICATE_API_TOKEN required).

6. **Save**:

  • Default: `./generated/upscaled/<input-stem>-4x.png` (or `-2x.png` / `-8x.png`)
  • Custom: `--output <path>`

MODES

Required

  • `upscaler --image <path-or-url>`

Options

  • `--scale 2|4|8` — upscaling factor (default 4)
  • `--output <path>` — explicit output path
  • `--replicate-model <id>` — override default upscaler model
  • `--face-enhance` — enable face restoration (works with Real-ESRGAN, GFPGAN)
  • `--yes` — skip cost confirmation
  • `--check` — verify REPLICATE_API_TOKEN + connectivity

REFERENCES (load on demand)

| File | When to load | |---|---| | [references/providers.md](references/providers.md) | Replicate upscaler model comparison + when to pick which | | [references/use-cases.md](references/use-cases.md) | Real-world scenarios (old photo restoration, product shots, low-res AI gen output) | | [references/troubleshoot.md](references/troubleshoot.md) | When output is blurry, faces get distorted, artifacts appear |

EXAMPLES

See [examples/before-after.md](examples/before-after.md) — 3 calibration runs: AI-gen image at higher resolution, old family photo restoration, product shot enhancement.

CONSTRAINTS

  • **Single image per call.** For batch: run in a shell loop.
  • **Replicate API key required.** Set via `/skills-keys add REPLICATE_API_TOKEN r8_...`.
  • **Cost**: ~$0.005-0.02 per image depending on model and scale. 4× cheapest; 8× ~3× more expensive.
  • **Input quality matters.** Models can enhance mildly-low-res images (480p → 1920p, soft → sharp). They CANNOT magic-restore severely degraded images.
  • **Face preservation**: use `--face-enhance` or switch to `--replicate-model tencentarc/gfpgan` for portraits. Without this, generic upscalers may distort facial features.
  • **Output dimensions** = input × scale factor. A 512×512 input at `--scale 4` → 2048×2048 output. Plan disk space.
  • **Output format is PNG by default.** Source format preserved when possible; transparent backgrounds maintained.
  • **Default 4×** is the most-supported scale across all upscalers. Some models don't support 8×.
  • **No re-encoding to JPEG by skill.** If you need JPEG: convert after via `magick` or Photoshop / Affinity.
  • **Never print API keys.**
  • **Output dir is `./generated/upscaled/`** by default.

INVOCATION HINTS

When the user says any of:

  • "upscale this image", "enhance the resolution"
  • "make this bigger / sharper", "fix this low-res image"
  • "4x upscale", "8x upscale"
  • "улучши разрешение", "увеличь фотку", "апскейл", "повысь разрешение"
  • "сделай четче"

Defaults: `--image <path>` (required); 4× via Real-ESRGAN; saves to `./generated/upscaled/<stem>-4x.png`.

For portrait / face photos: prefer `--face-enhance` or `--replicate-model tencentarc/gfpgan`.

For AI-gen output to upscale: default (Real-ESRGAN) works well; the model is trained on a mix of real + AI imagery.

This skill is distinct from:

  • `image-prompt` / `cover-maker` / etc. — they GENERATE new images. This ENHANCES existing.
  • `bg-remover` — that's segmentation (transparent BG). This is super-resolution.
  • `style-transfer` (planned) — that's stylization. This is resolution.
  • `style-check` etc. — those are text linters, not visual utilities.
Read more
@mikefluff
Ships withskills

45 skills for Claude Code that make content — and refuse to let it read like a machine made it. Prose editing that strips the tells. Prompt engineering for 40+ image, video and music models, with optional one-command execution against the real APIs.

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Questions about upscaler.

Which coding agents can use upscaler?
upscaler installs in Claude Code, Codex, Cursor, Gemini CLI, GitHub Copilot, OpenCode and Windsurf with the skills CLI, using each agent's flag shown on this page. Flowy's auto-invocation, which fires a skill when your prompt matches, runs in Claude Code only.