image-compression（图像压缩）

Platform Notes

• Optional helper plugins may help in some environments, but they must not be treated as required for this skill.

Image Compression

Acknowledgement: Shared by Peter Bamuhigire, techguypeter.com, +256 784 464178.

Use When

• Client-side image compression before upload using Squoosh with Canvas fallback and server-side Sharp validation. Use for web apps needing max width 1920px, max size 512KB, transparent UX, and consistent compression stats.
• The task needs reusable judgment, domain constraints, or a proven workflow rather than ad hoc advice.

Do Not Use When

• The task is unrelated to image-compression or would be better handled by a more specific companion skill.
• The request only needs a trivial answer and none of this skill's constraints or references materially help.

Required Inputs

• Gather relevant project context, constraints, and the concrete problem to solve; load references only as needed.
• Confirm the desired deliverable: design, code, review, migration plan, audit, or documentation.

Workflow

• Read this SKILL.md first, then load only the referenced deep-dive files that are necessary for the task.
• Apply the ordered guidance, checklists, and decision rules in this skill instead of cherry-picking isolated snippets.
• Produce the deliverable with assumptions, risks, and follow-up work made explicit when they matter.

Quality Standards

• Keep outputs execution-oriented, concise, and aligned with the repository's baseline engineering standards.
• Preserve compatibility with existing project conventions unless the skill explicitly requires a stronger standard.
• Prefer deterministic, reviewable steps over vague advice or tool-specific magic.

Anti-Patterns

• Treating examples as copy-paste truth without checking fit, constraints, or failure modes.
• Loading every reference file by default instead of using progressive disclosure.

Outputs

• A concrete result that fits the task: implementation guidance, review findings, architecture decisions, templates, or generated artifacts.
• Clear assumptions, tradeoffs, or unresolved gaps when the task cannot be completed from available context alone.
• References used, companion skills, or follow-up actions when they materially improve execution.

Evidence Produced

References

• Use the references/ directory for deep detail after reading the core workflow below.

Seamless image compression prior to upload with a hybrid approach:

• Client primary: Squoosh (WASM)
• Client fallback: Canvas API
• Server safety net: Sharp

Defaults: max width $1920$px, max size $512$ KB, quality $75$ (adjust down to hit size).

When to Use

✅ Web apps that upload user images and must reduce bandwidth ✅ Need transparent UX (no user action) ✅ Want modern codecs but must support older browsers

When Not to Use

❌ Server-only batch pipelines (use Sharp directly) ❌ Large-scale media processing with complex transforms (use ImageMagick/FFmpeg)

Core Rules

1. Maintain aspect ratio; never upscale.
2. Target max width $1920$px and max size $512$ KB.
3. Start at quality $75$; reduce in steps to meet size.
4. Prefer JPEG for compatibility; try WebP if size remains too large.
5. Log compression stats (ratio, saved, processing time).

Decision Flow

1. Client attempt (Squoosh)

- Resize → compress → check size. - Decrease quality until size limit met. - If still too large, try WebP.

1. Client fallback (Canvas)

- Resize → toBlob JPEG → reduce quality if needed.

1. Server fallback (Sharp)

- Always validate size/dimensions server-side. - Re-compress if client output exceeds limits.

Implementation Steps (High Level)

1. Client compression service

- Expose compressImage(file, options). - Use Squoosh with dynamic import. - Fallback to Canvas on error.

1. Upload hook / handler

- Validate input is image. - Compress transparently. - Upload compressed blob.

1. Server middleware

- Use Sharp to enforce limits. - Return 413 if still too large. - Attach compression stats to logs.

Required Defaults

• maxWidth: 1920
• maxHeight: 1920
• maxSize: $512 * 1024$
• quality: 75
• minDimensions: 200x200 (server-side)

Anti-Patterns

• ❌ Skipping server validation
• ❌ Uploading original file on failure without logging
• ❌ Enlarging images
• ❌ Using blocking UI (must be transparent to user)

References (Load as Needed)

• Client implementation: references/client.md
• Client usage example: references/client-usage.md
• Server middleware + routes: references/server.md
• Storage adapters (S3/local): references/storage.md
• Security checks: references/security.md
• Monitoring & analytics: references/monitoring.md
• Performance targets: references/performance.md
• Quality examples: references/quality-metrics.md
• Environment variables: references/env.md
• Docker (Sharp): references/docker.md
• Implementation checklist: references/implementation-checklist.md

Output Expectations

• Client compression completes in $100$–$500$ ms typical
• Server compression $50$–$200$ ms typical
• Bandwidth reduction $85$–$97%$

Checklist

• Client: Squoosh primary + Canvas fallback
• Client: size/dimension limits enforced
• Server: Sharp validation + compression
• Logging: compression stats & processing time
• Storage: image saved with metadata
• Tests: JPEG/PNG/WebP, large images, mobile