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SKILL verified MIT Self-run

Bg Remover

skill-mikefluff-skills-bg-remover · by Mikefluff

Background removal utility — image in, transparent PNG out. Wraps Replicate-hosted models (851-labs/background-remover default; alternatives via --replicate-model). Use when: 'remove the background', 'cut out the subject', 'transparent PNG', 'убери фон', 'вырежи фон с фотки'.

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Install

$ agentstack add skill-mikefluff-skills-bg-remover

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

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

Security review passed
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2d ago

Declared compatibility

Claude CodeClaude Desktop

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

Preview Execution monitoring

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About

Remove the background from a photo. Single input image → output PNG with transparent (alpha channel) background. Subject preserved as-is; everything else becomes transparent.

This skill does NOT:

  • Replace the background with a new image — for that, use the transparent PNG output + paste into a new background in your image editor, OR use image-prompt --execute --model flux-kontext --image-url --prompt "subject in new setting" for full reimagining
  • Remove specific objects from a complex scene — only removes BACKGROUND (everything not the main subject)
  • Process video — single image only (per call)
  • Restore / upscale / sharpen — see future upscaler skill

ROLE

Read the input image → call a Replicate-hosted bg-removal model → save the transparent PNG.

PIPELINE

  1. Resolve input:
  • --image (required)
  • Local file or remote URL
  1. Pick provider:
  • Default: 851-labs/background-remover (popular, accurate on photos)
  • Alternatives via --replicate-model :
  • 851-labs/background-remover — default; best general
  • lucataco/remove-bg — alternative
  • cjwbw/rembg — Python rembg library hosted
  • pollinations/modnet — MODNet (good for portraits)
  • Other Replicate bg-removers: pass via --replicate-model
  1. Execute via the Replicate router (REPLICATEAPITOKEN required).
  1. Save:
  • Default: ./generated/bg-removed/-nobg.png (transparent)
  • Custom: --output

MODES

Required

  • bg-remover --image

Options

  • --output — explicit output path
  • --replicate-model — override default bg-remover model
  • --execute — defaults to true (this skill always executes; no prompt-only mode for a utility)
  • --yes — skip cost confirmation
  • --check — verify REPLICATEAPITOKEN + connectivity

REFERENCES (load on demand)

| File | When to load | |---|---| | [references/providers.md](references/providers.md) | Replicate bg-removal model comparison + when to pick which | | [references/output-format.md](references/output-format.md) | Transparent PNG handling, alpha channel, downstream usage | | [references/troubleshoot.md](references/troubleshoot.md) | When subject loses edges, hair gets cropped, etc. |

EXAMPLES

See [examples/before-after.md](examples/before-after.md) — 2 calibration runs: portrait photo → transparent for avatar use; product shot → transparent for e-commerce listing.

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: ~$0.001-0.005 per image depending on model. Very cheap.
  • Default model handles most photos well. Switch to pollinations/modnet for portraits if hair edges are critical.
  • Subject must be CLEARLY distinguishable from background. Models struggle with:
  • Subjects that match background color
  • Multiple subjects (picks one or merges)
  • Transparent objects (glass / water)
  • Hair against busy backgrounds (some loss of fine detail expected)
  • Output is always PNG with alpha channel. RGB → RGBA conversion automatic.
  • Source resolution preserved. Output dimensions match input.
  • No re-encoding to JPEG. Transparent backgrounds require PNG (or WebP) — JPEG doesn't support transparency.
  • Never print API keys.
  • Output dir is ./generated/bg-removed/ by default.

INVOCATION HINTS

When the user says any of:

  • "remove the background", "cut out the subject"
  • "transparent PNG", "no background version"
  • "убери фон", "вырежи фон с фотки", "сделай прозрачный фон"
  • "make the background transparent"

Defaults: --image (required); auto-saves to ./generated/bg-removed/-nobg.png.

If the user wants to REPLACE the background (not just remove), suggest:

  1. Use this skill to get a transparent PNG.
  2. Then use image-prompt --execute --model flux-kontext --image-url for AI-driven replacement.
  3. OR open the transparent PNG in an image editor and composite with a new background manually.

This skill is distinct from:

  • image-prompt / avatar-maker — they generate NEW images. This is a utility on EXISTING images.
  • subtitle-burner — that's video utility. This is image utility.
  • upscaler (planned) — that's resolution. This is background removal.

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.