Prismer Cloud is an infrastructure layer for AI agents that provides shared learning, compressed context, persistent memory, collaboration, messaging, tasks, identity, and workspaces. It is for agents and the people building or using long-running agent systems that need information and outcomes to persist across sessions. The catalogue entries provide skills, hooks, agents, instructions, and a plugin for using Prismer Cloud.
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 Prismer-AI/PrismerCloud --skill image-generategit clone --depth 1 https://github.com/Prismer-AI/PrismerCloudWrote 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/prismer-ai/prismercloud/image-generate)<a href="https://agentmods.dev/skills/prismer-ai/prismercloud/image-generate"><img src="https://agentmods.dev/badge/skills/prismer-ai/prismercloud/image-generate.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00103 | $0.03685 |
| Opus 5 | $0.00051 | $0.01843 |
| Sonnet 5 | $0.00021 | $0.00737 |
| Haiku 4.5 | $0.00010 | $0.00368 |
Grade A, and why
image-generate 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 8d 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 — 328 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Generate
Turn a text prompt into a content-addressed image asset plus a v2.0 §4.6 ContentBlock that the chat renderer can surface inline. The skill is a thin orchestration over two existing surfaces:
- LLM image gateway — the cloud's NewAPI proxy at
POST /api/v1/images/generations(OpenAI-compatible — see §"Hand-off" if the endpoint is not yet wired in your deployment). - Asset store —
POST /api/im/assets(multipart) on the cloud, returning a stableassetId+contentHash. Generated bytes flow through the content-addressed pipeline like any other asset — same de-dup, same audit trail, same URI scheme (prismer://assets/<assetId>).
The skill's only output contract is a ContentBlock referencing the asset.
Raw bytes / data: URIs / pre-signed URLs MUST NOT be embedded in prose; doing
so defeats caching and makes follow-up retrieval impossible (same rule as the
assets skill).
When to use
- The user says "draw", "generate an image of …", "make me a picture / poster / diagram / illustration".
- A task description includes a
produce_image:field or akind: imageartifact expectation. - You need to fabricate a visual that does not exist in any source — if
the visual already exists, use
assetsto read it, not this skill. - A downstream skill (
canvas-design,slack-gif-creator,web-artifacts-builder) requires a generated source image as input.
Not when to use
- Editing / variation / inpainting an existing image — that's a separate
upcoming skill (
image-edit). Don't fake it by reading + regenerating. - Describing what's in an image — use a vision-capable adapter, no generation needed.
- Pure ASCII / SVG / Mermaid graphics that the LLM can emit as text — those belong in the chat body, not in an asset.
- Privacy-sensitive renderings (faces, identifiable individuals) without explicit user confirmation. The skill does not gate this; the agent must.
API Reference
There is no cloud image generate subcommand in the runtime CLI today
(release 201 audit, sdk/prismer-cloud/runtime/src/cli/commands/). Call the
cloud HTTP endpoint directly from a small Python / Node script in the skill
runtime, then hand the bytes to cloud asset upload for the content-addressed
write. Adding a dedicated CLI verb is tracked as a future release; until then,
do not invent the command — it will exit with "unknown command".
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.
- 8d ago First seen · 328 lines · 103 tokens per session scan A 4dfe32d470ef
image-generate is a skill published in the GitHub repository Prismer-AI/PrismerCloud (1,410 stars, last pushed 1mo ago), licensed MIT. It adds 103 tokens to every session and 3,685 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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