Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/buildoak/fieldwork-skillsnpx agentmods add skills/buildoak/fieldwork-skills/image-genWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/buildoak/fieldwork-skills/image-gen)<a href="https://agentmods.dev/skills/buildoak/fieldwork-skills/image-gen"><img src="https://agentmods.dev/badge/skills/buildoak/fieldwork-skills/image-gen/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/buildoak/fieldwork-skills/image-gen"><img src="https://agentmods.dev/badge/skills/buildoak/fieldwork-skills/image-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What 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 5.1 | $0.00079 | $0.05085 |
| Opus 5.5 | $0.00032 | $0.02034 |
| Sonnet 5.5 | $0.00016 | $0.01017 |
| Haiku 4.5 | $0.00008 | $0.00509 |
Grade A, and why
image-gen scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -fsSL https://raw.githubusercontent.com/buildoak/fieldwork-skills/main/skills/image-gen/UPDATES.md | head -40 How it starts
The opening of the file, as written. The whole thing — 576 lines — stays where its author put it; the contents beside it link to each section on GitHub.
image-gen
Image generation and editing via OpenRouter. Five models, three scripts, style presets, one JSON contract.
Scripts: ./scripts/generate.py, ./scripts/edit.py, ./scripts/review.py
Presets: ./presets/*.json
Output dir: ./data/
Setup
export OPENROUTER_API_KEY_IMAGES='your-api-key-here'
- Claude Code: copy this skill folder into
.claude/skills/image-gen/ - Codex CLI: append this SKILL.md content to your project's root
AGENTS.md
For the full installation walkthrough (prerequisites, API keys, verification, troubleshooting), see references/installation-guide.md.
Credential management
Three tiers for managing the OPENROUTER_API_KEY_IMAGES environment variable:
- Vault skill (recommended): If you have a vault or secret-management skill, store the key there and export it before running scripts. Example:
export OPENROUTER_API_KEY_IMAGES=$(vault get OPENROUTER_API_KEY_IMAGES) - Custom secret manager: Use your team's preferred secret manager (1Password CLI, AWS Secrets Manager, etc.)
- Plain export:
export OPENROUTER_API_KEY_IMAGES='your-api-key-here'in your shell profile
Optional keys for additional features:
OPENAI_API_KEY-- for mask-based inpainting viaedit.py --mode openaiANTHROPIC_API_KEY-- for auto-review viareview.py --auto
Model Selection
What do you need?
|
+-- Fast + cheap + good enough?
| --> nanobanana (~$0.0004/image)
|
+-- High quality, no text?
| --> flux.2-pro (best visual quality)
|
+-- Text in the image?
| --> gpt-5-image (best text rendering)
|
+-- Image editing?
| +-- Describe changes in words --> gpt-5-image or nanobanana-pro
| +-- Paint mask area to change --> edit.py --mode openai
|
+-- Budget generation at scale?
| --> flux.2-klein (fastest, cheapest Flux)
|
+-- Quality + editing + reasoning?
--> nanobanana-pro (best balance)
What ships with it
17 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.
- .gitignore 73 B
- examples/flux-2-pro-example-1.jpg 318 KB
- examples/flux-2-pro-example-2.jpg 390 KB
- examples/nanobanana-pro-example-1.jpg 501 KB
- presets/default.json 322 B
- README.md 1.9 KB
- references/api-reference.md 6.5 KB
- references/book-to-prompts-playbook.md 27 KB
- references/installation-guide.md 3.3 KB
- references/model-card.md 5.2 KB
- references/prompt-templates.md 18 KB
- references/style-consistency.md 3.2 KB
- scripts/edit.py 14 KB runs code
- scripts/generate.py 23 KB runs code
- scripts/review.py 6.6 KB runs code
- UPDATE-GUIDE.md 1.7 KB
- UPDATES.md 3.4 KB
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.
- 1mo ago First seen · 576 lines · 79 tokens per session scan A f3484404736b
image-gen is a skill published in the GitHub repository buildoak/fieldwork-skills (15 stars, last pushed 7mo ago), licensed Apache-2.0. It adds 79 tokens to every session and 5,085 once invoked, about $0.0003 per session on Opus 5.5. 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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