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Get Started Free →Generate images using AI agents on Fetch.ai's Agentverse. Sends a text prompt to an image generation agent and returns the generated image URL. Handles agent discovery, relay deployment, and response parsing automatically. Requires AGENTVERSE_API_KEY env var. Use when asked to generate, create, or make an image via Agentverse.
.claude/skills/fetchai-agentverse-image-gen/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-02 | ✗→✓ | ▲ Improved | 136% | 0% |
| case-04 | ✗→✓ | ▲ Improved | -10% | 0% |
| case-06 | ✗→✓ | ▲ Improved | 28% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 44% | 0% |
| case-08 | ✗→✓ | ▲ Improved | 33% | 0% |
Generate images by sending text prompts to AI image generation agents on Agentverse. Returns a public URL to the generated image. Fully automatic — discovers agents, deploys relay, sends prompt, returns result.
AGENTVERSE_API_KEY environment variable setrequestsbashpython3 scripts/generate_image.py \ --prompt "A futuristic AI robot launching a rocket from a launchpad, cyberpunk style, neon colors" \ --wait 60
bashpython3 scripts/generate_image.py \ --prompt "A dragon made of circuit boards on a Tokyo rooftop at sunset" \ --agent "agent1qdynamic8lgnax37n20296xr4kcfllahlnse7gy5mrkdt4q9v9h06qkmclkl" \ --wait 60
When the image comes back as a CDN URL (e.g. Cloudinary), image_url is already browser-openable:
json{ "status": "success", "prompt": "A dragon made of circuit boards...", "image_url": "https://res.cloudinary.com/fetch-ai/image/upload/v1776700090/dalle3-agent/0932ec14-...", "metadata": {}, "target_agent": "agent1q0utywlfr3dfrfkwk4fjmtdrfew0zh692untdlr877d6ay8ykwpewydmxtl", "relay_agent": "agent1q...", "wait_time_seconds": 35, "all_responses": [{"type": "text", "text": "Generating..."}, "..."] }
When the image comes back as an agent-storage:// URI, the response also includes public_url — a direct HTTPS URL you can open in a browser or download:
json{ "status": "success", "prompt": "A sunset over Tokyo", "image_url": "agent-storage://https://agentverse.ai/v1/storage/47cecfda-8d6f-4c21-80ab-10c4d8d052bb", "public_url": "https://agentverse.ai/v1/storage/47cecfda-8d6f-4c21-80ab-10c4d8d052bb", "metadata": {"mime_type": "image/png", "role": "generated-image"}, "target_agent": "agent1q0utywlfr3dfrfkwk4fjmtdrfew0zh692untdlr877d6ay8ykwpewydmxtl", "relay_agent": "agent1q...", "wait_time_seconds": 45, "all_responses": [...] }
> Use public_url (when present) to open or display the image. Fall back to image_url for CDN-hosted images.
--agent specified, searches for image generation agentsChatMessage with your prompt as TextContentResourceContent from response logsIf you don't specify --agent, the script uses the well-known Fetch.ai DALL-E 3 image agent:
agent1q0utywlfr3dfrfkwk4fjmtdrfew0zh692untdlr877d6ay8ykwpewydmxtlThis agent generates images using DALL-E 3 and returns them as Cloudinary URLs.
--waitagentverse-search to find alternative image agentsagentverse-chat pattern internally| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-23 | fail→fail | 11,042 | 7,027 | -36% | 1 | 1 | 0% | 2,077 | 2,628 | +27% | 0 | 0 | — |
case-01 | fail→fail | 5,921 | 1,617 | -73% | 1 | 1 | 0% | 1,103 | 1,505 | +36% | 0 | 0 | — |
case-02 | fail→pass | 5,747 | 5,391 | -6% | 1 | 1 | 0% | 969 | 2,283 | +136% | 0 | 0 | — |
case-03 | fail→fail | 9,174 | 4,479 | -51% | 1 | 1 | 0% | 1,765 | 1,521 | -14% | 0 | 0 | — |
case-04 | fail→pass | 9,997 | 1,532 | -85% | 1 | 1 | 0% | 1,686 | 1,523 | -10% | 0 | 0 | — |
case-05 | pass→pass | 5,024 | 1,986 | -60% | 1 | 1 | 0% | 801 | 1,622 | +102% | 0 | 0 | — |
case-06 | fail→pass | 7,548 | 2,593 | -66% | 1 | 1 | 0% | 1,337 | 1,718 | +28% | 0 | 0 | — |
case-07 | fail→pass | 6,789 | 2,394 | -65% | 1 | 1 | 0% | 1,228 | 1,764 | +44% | 0 | 0 | — |
case-08 | fail→pass | 5,852 | 2,977 | -49% | 1 | 1 | 0% | 1,052 | 1,400 | +33% | 0 | 0 | — |
case-09 | pass→pass | 5,406 | 1,365 | -75% | 1 | 1 | 0% | 829 | 1,415 | +71% | 0 | 0 | — |
case-10 | pass→pass | 10,158 | 2,908 | -71% | 1 | 1 | 0% | 1,899 | 1,879 | -1% | 0 | 0 | — |
case-11 | fail→pass | 12,067 | 3,758 | -69% | 1 | 1 | 0% | 1,988 | 1,639 | -18% | 0 | 0 | — |
case-12 | fail→pass | 12,723 | 2,691 | -79% | 1 | 1 | 0% | 2,580 | 1,863 | -28% | 0 | 0 | — |
case-13 | fail→pass | 7,556 | 1,763 | -77% | 1 | 1 | 0% | 1,347 | 1,511 | +12% | 0 | 0 | — |
case-14 | fail→pass | 7,745 | 1,501 | -81% | 1 | 1 | 0% | 1,440 | 1,458 | +1% | 0 | 0 | — |
case-15 | fail→pass | 14,416 | 2,789 | -81% | 1 | 1 | 0% | 2,736 | 1,793 | -34% | 0 | 0 | — |
case-16 | fail→pass | 11,666 | 3,201 | -73% | 1 | 1 | 0% | 2,320 | 1,807 | -22% | 0 | 0 | — |
case-17 | fail→pass | 12,693 | 1,192 | -91% | 1 | 1 | 0% | 773 | 1,431 | +85% | 0 | 0 | — |
case-18 | fail→pass | 6,086 | 1,438 | -76% | 1 | 1 | 0% | 1,076 | 1,503 | +40% | 0 | 0 | — |
case-19 | fail→pass | 11,039 | 3,215 | -71% | 1 | 1 | 0% | 1,874 | 1,871 | -0% | 0 | 0 | — |
case-20 | fail→pass | 8,120 | 3,202 | -61% | 1 | 1 | 0% | 1,445 | 1,893 | +31% | 0 | 0 | — |
case-21 | fail→fail | 8,696 | 6,918 | -20% | 1 | 1 | 0% | 1,652 | 2,571 | +56% | 0 | 0 | — |
case-22 | pass→pass | 14,712 | 9,892 | -33% | 1 | 1 | 0% | 3,136 | 3,532 | +13% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 23 cases were attempted, and 21 counted toward the lift figure. The other 2 produced results that are not comparable between the two arms, so they are excluded from the headline rather than averaged into it. The headline lift of +65 percentage points is the difference between those two pass rates over the 21 comparable cases.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.