Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/gaelic-ghost/socket/apple-image-representation-workflownpx skills add gaelic-ghost/socket --skill apple-image-representation-workflowgit clone --depth 1 https://github.com/gaelic-ghost/socketWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00081 | $0.01263 |
| Opus 5 | $0.00041 | $0.00632 |
| Sonnet 5 | $0.00016 | $0.00253 |
| Haiku 4.5 | $0.00008 | $0.00126 |
Grade A, and why
apple-image-representation-workflow scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Apple Image Representation Workflow
Purpose
Guide image source, destination, representation, and conversion work without flattening distinct Apple image types into a generic wrapper. Keep file encoding, rendered pixels, processing recipes, platform display containers, metadata, and auxiliary images visibly separate.
When To Use
- Use for Image I/O sources and destinations, metadata, thumbnails, incremental loading, multi-frame images,
CGImage,NSImage,NSImageRep,NSBitmapImageRep,UIImage, and representation conversion. - Recommend
core-image-processing-workflowwhen filters, compositing, RAW development, custom kernels, or rendering are primary. - Recommend the Vision workflow when the requested outcome is recognition or analysis rather than representation ownership.
Single-Path Workflow
- Classify the request:
- source inspection or decoding
- incremental loading or thumbnailing
- metadata or auxiliary data
- destination encoding or multi-frame output
- Core Graphics raster ownership
- AppKit representation or drawing
- UIKit image display ownership
- conversion or repair
- Apply the Apple docs gate:
- read current Image I/O, Core Graphics, AppKit, or UIKit documentation first
- state the documented behavior relied on
- check API, image-format, auxiliary-data, and platform availability before promising a decode, encode, or representation path
- apply
../../shared/references/apple-image-type-ownership.md - use
references/image-io-decoding-encoding-and-metadata.mdfor source and destination work - use
references/apple-image-representations-and-bridging.mdfor type selection and conversion
- Preserve source meaning:
- inspect type, frame count, dimensions, properties, orientation, color profile, alpha, dynamic range, and auxiliary data before conversion
- choose decode-time thumbnailing or incremental loading when the workload requires it
- identify whether metadata and original encoded bytes must survive
- Choose the representation:
CGImagefor concrete raster pixels and Core Graphics drawingCIImagefor a lazy processing graphNSImageandNSImageRepfor macOS display-oriented multi-representation behaviorUIImagefor UIKit display semantics including scale and orientationCVPixelBufferfor frame-oriented media and hardware interop
- Encode deliberately:
- choose destination type, frame count, properties, metadata policy, orientation policy, color profile, compression, and auxiliary-data policy
- add every image or frame
- require successful
CGImageDestinationFinalizebefore claiming output exists
- Return one recommendation with source facts, chosen types, conversion losses, decode/encode plan, memory and cancellation policy, diagnostics, and validation.
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 93 lines · 81 tokens per session scan A 70c388654cf1
apple-image-representation-workflow is a skill published in the GitHub repository gaelic-ghost/socket (7 stars, last pushed 6d ago), licensed Apache-2.0. It adds 81 tokens to every session and 1,263 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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