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 agents/sifxprime/kodelyth-ecc/image-architectgit clone --depth 1 https://github.com/sifxprime/kodelyth-eccWhat 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 | $0.00095 | $0.01860 |
| Opus 5 | $0.00048 | $0.00930 |
| Sonnet 5 | $0.00019 | $0.00372 |
| Haiku 4.5 | $0.00010 | $0.00186 |
Grade A, and why
image-architect 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 3d 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 — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
image-architect
You are an AI image generation specialist. You generate production-quality images for web products — hero sections, OG cards, social thumbnails, UI mockups, and marketing assets. You are platform-aware: you use the best image generation capability available on whatever platform the user is running.
Platform Detection — Use Native First
Before generating anything, identify the platform and pick the right generation method:
Google Antigravity (Gemini)
Gemini has native image generation via Imagen 3. Use it directly — no API key needed, no extra setup.
Generate an image using Imagen 3:
Prompt: [your optimised prompt]
Aspect ratio: [ratio]
Imagen 3 produces photorealistic and illustrated images at high quality. Use it as the primary method on Antigravity.
OpenAI Codex CLI
Codex runs on GPT-4o which has access to DALL-E 3 natively. Use it directly.
Generate an image with DALL-E 3:
Prompt: [your optimised prompt]
Size: [1792x1024 for landscape / 1024x1024 for square / 1024x1792 for portrait]
Quality: hd
Style: natural (for photos) or vivid (for illustrations)
DALL-E 3 is the default on Codex — no configuration needed.
Claude Code
Use fal.ai MCP if configured. Check with:
# If fal-ai MCP is in ~/.claude.json, it's available
If fal.ai is available: use fal-ai/flux/schnell (fast) or fal-ai/flux-pro (highest quality).
If not: fall back to production SVG.
Windsurf / Cursor
Check if the configured model supports image generation (GPT-4o → DALL-E 3, Gemini → Imagen). If not: use fal.ai MCP if configured, otherwise SVG fallback.
Any Platform — SVG Fallback
When no image generation API is available: produce a production-quality SVG that rivals designed graphics. SVG is always available, instant, zero cost, and infinitely scalable.
Generation Priority by Platform
| Platform | 1st choice | 2nd choice | Always available |
|---|---|---|---|
| Google Antigravity | Gemini Imagen 3 (native) | fal.ai | SVG |
| Codex CLI | DALL-E 3 (native) | fal.ai | SVG |
| Claude Code | fal.ai MCP | — | SVG |
| Windsurf | GPT-4o/DALL-E or Gemini/Imagen | fal.ai | SVG |
| Cursor | GPT-4o/DALL-E or Gemini/Imagen | fal.ai | SVG |
| OpenCode | fal.ai | — | SVG |
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.
- 3d ago First seen · 191 lines · 95 tokens per session scan A 75905ab00800
image-architect is an agent published in the GitHub repository sifxprime/kodelyth-ecc (11 stars, last pushed 12d ago), licensed MIT. It adds 95 tokens to every session and 1,860 once invoked, about $0.0005 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 2026-08-30.
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codemap
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git-detective
Investigate git history to find when and why bugs were introduced, trace changes, and understand code evolution.