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 commands/deapi-ai/claude-code-skills/transform-imagegit clone --depth 1 https://github.com/deapi-ai/claude-code-skillsWhat 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 | $0.00011 | $0.00989 |
| Opus 5 | $0.00005 | $0.00495 |
| Sonnet 5 | $0.00002 | $0.00198 |
| Haiku 4.5 | $0.00001 | $0.00099 |
Grade A, and why
transform-image scanned grade A with 1 finding 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -o /tmp/transform_image1.png "{image_url_1}" How it starts
The opening of the file, as written. The whole thing — 109 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Transformation via deAPI
Transform image: $ARGUMENTS
Step 1: Parse arguments
Extract from $ARGUMENTS:
image_url: URL(s) to source image(s) - Klein supports up to 3 images (required)style_prompt: Description of desired transformation (required)--model:klein(default, faster, multi-image) orqwen(higher steps, more control)
Example style prompts:
- "convert to watercolor painting"
- "make it look like a vintage photograph"
- "transform into anime style"
- "add cyberpunk neon aesthetic"
- "combine these images into one scene" (multi-image with Klein)
Step 2: Send request
Note: This endpoint requires multipart/form-data with file upload.
If user provides URL(s), first download the image(s):
curl -s -o /tmp/transform_image1.png "{image_url_1}"
curl -s -o /tmp/transform_image2.png "{image_url_2}" # optional
curl -s -o /tmp/transform_image3.png "{image_url_3}" # optional
Then send the transformation request:
curl -s -X POST "https://api.deapi.ai/api/v1/client/img2img" \
-H "Authorization: Bearer $DEAPI_API_KEY" \
-F "image=@{local_file_path_1}" \
-F "image=@{local_file_path_2}" \
-F "image=@{local_file_path_3}" \
-F "prompt={style_prompt}" \
-F "model={model_name}" \
-F "guidance={guidance}" \
-F "steps={steps}" \
-F "seed={random_seed}"
Model mapping:
| User flag | API model name | Steps | Guidance | Max images | Info |
|---|---|---|---|---|---|
klein (default) |
Flux_2_Klein_4B_BF16 |
4 (fixed) | ignored | 3 | Faster, multi-image support |
qwen |
QwenImageEdit_Plus_NF4 |
10-50 (default: 20) | 7.5 | 1 | More control, higher fidelity |
Klein model limits:
- Resolution: 256-1536px (step: 16)
- Steps: 4 (fixed)
- Guidance: not supported
- Max input images: 3
Parameters:
| Parameter | Klein | Qwen | Description |
|---|---|---|---|
guidance |
ignored | 7.5 | Prompt adherence (1-20) |
steps |
4 (fixed) | 20 | Inference steps |
seed |
random | random | For reproducibility (0-999999) |
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 · 109 lines · 11 tokens per session scan A ec0b09f312bf
transform-image is a command published in the GitHub repository deapi-ai/claude-code-skills (21 stars, last pushed 2mo ago), licensed MIT. It adds 11 tokens to every session and 989 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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tray-referencia-api
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learn
Capture what the user changed in a draft the skill wrote, so the loop can learn from it. Every rewrite, cut, or addition is evidence; this command turns it into ledger records that /humanise improve mines for rule-change candidates.