ClawRouter is a local service that chooses among language models for each request and handles payment for their use. Autonomous agents use it to access multiple LLM providers through one routing and billing system.
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 skills add BlockRunAI/ClawRouter --skill imagegengit clone --depth 1 https://github.com/BlockRunAI/ClawRouterWrote 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/blockrunai/clawrouter/imagegen)<a href="https://agentmods.dev/skills/blockrunai/clawrouter/imagegen"><img src="https://agentmods.dev/badge/skills/blockrunai/clawrouter/imagegen/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/blockrunai/clawrouter/imagegen"><img src="https://agentmods.dev/badge/skills/blockrunai/clawrouter/imagegen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 7 findings, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium Prompt Injection · line 58 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 60 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 62 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 63 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 66 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 67 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 68 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
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 | $0.00045 | $0.02206 |
| Opus 5.5 | $0.00018 | $0.00882 |
| Sonnet 5.5 | $0.00009 | $0.00441 |
| Haiku 4.5 | $0.00005 | $0.00221 |
Grade A, and why
imagegen 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 yesterday.
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 — 151 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Generation & Editing
Generate or edit images through ClawRouter. Payment is automatic via x402.
Shortcuts:
- Slash:
/cr-imagegen <prompt> [--model=<alias>] [--size=1024x1024] [--n=1](/imagegenstill accepted in chat for backward compatibility) - Partner tool:
blockrun_image_generation(LLM-callable) /blockrun_image_edit(inpainting)
Generate an Image
POST to http://localhost:8402/v1/images/generations:
{
"model": "google/nano-banana",
"prompt": "a golden retriever surfing on a wave",
"size": "1024x1024",
"n": 1
}
Response:
{
"created": 1741460000,
"data": [{ "url": "http://localhost:8402/images/abc123.png" }]
}
Display inline: 
Model Selection
| Alias | Full ID | Sizes | Best for |
|---|---|---|---|
nano-banana |
google/nano-banana |
1024×1024 | Default — fast, cheap, good quality |
banana-2 |
google/nano-banana-2 |
1024×1024 | Gemini 3.1 Flash imagegen — sharper than nano-banana at 1K |
banana-pro |
google/nano-banana-pro |
1024×1024, 2048×2048, 4096×4096 | High-res, large format |
gpt-image |
openai/gpt-image-1 |
1024×1024, 1536×1024, 1024×1536 | Budget option; supports editing |
gpt-image-2 |
openai/gpt-image-2 |
1024×1024, 1536×1024, 1024×1536 | Photorealistic, reasoning-driven, text rendering (slow — proxy polls up to 5min); legacy dalle alias routes here |
flare |
openai/gpt-image-2.5-flare |
1024×1024, 1536×1024, 1024×1536 | GPT Image 2.5, fast — top OpenAI quality, caller can pick quality at a flat price |
sunburst |
openai/gpt-image-2.5-sunburst |
1024×1024, 1536×1024, 1024×1536 | GPT Image 2.5, precision — best for high-fidelity edits |
seedream |
bytedance/seedream-5-pro |
up to 2848×1600 / 2304×1728 | Flagship quality, reference-image support |
grok-imagine |
xai/grok-imagine-image |
1024×1024 | xAI Grok image style |
grok-imagine-2 |
xai/grok-imagine-image-2.0 |
1024×1024 | Grok Imagine 2.0 — between grok-imagine and pro |
grok-imagine-pro |
xai/grok-imagine-image-pro |
1024×1024 | Grok high-quality |
cogview |
zai/cogview-4 |
512×512 to 1440×1440 | Cheapest — Zhipu CogView |
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.
- yesterday Changed · +2 lines 2f53058a12a9
- 22d ago Changed · +4 lines db65e85e15a9
- 1mo ago Changed 016966af7f0f
- 1mo ago First seen · 145 lines · 45 tokens per session scan A 39663f6e7a3c
imagegen is a skill published in the GitHub repository BlockRunAI/ClawRouter (6,635 stars, last pushed yesterday), licensed MIT. It adds 45 tokens to every session and 2,206 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
route
Route a task to the best LLM based on task type and complexity.
routing
Route tasks to the cheapest capable model automatically using llmrouter MCP tools.
savings
Report how much routing has saved by sending tasks to cheaper models.
energy-expert
Expert-level energy systems, smart grids, renewable energy, power management, and energy analytics. Use when the user mentions smart grid, renewable, power, utilities, or SCADA, or when the task involves Energy Systems, Smart Grid Technology, Standards and Protocols, or Smart Grid Operations.
manufacturing-expert
Expert-level manufacturing systems, Industry 4.0, production optimization, quality control, and smart factory solutions. Use when the user mentions Industry 4.0, production, quality, MES, or PLCs, or when the task involves Manufacturing Systems, Standards and Protocols, Production Management, or Quality Management.
trading-expert
Expert-level algorithmic trading, market systems, quantitative analysis, and trading platforms. Use when the user mentions algorithmic trading, quant, markets, finance, or high-frequency trading, or when the task involves Trading Systems, Market Data, or Execution.