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/blockrun-mcp --skill image-promptinggit clone --depth 1 https://github.com/BlockRunAI/blockrun-mcpWrote 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/blockrun-mcp/image-prompting)<a href="https://agentmods.dev/skills/blockrunai/blockrun-mcp/image-prompting"><img src="https://agentmods.dev/badge/skills/blockrunai/blockrun-mcp/image-prompting/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/blockrun-mcp/image-prompting"><img src="https://agentmods.dev/badge/skills/blockrunai/blockrun-mcp/image-prompting.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00079 | $0.03820 |
| Opus 5.5 | $0.00032 | $0.01528 |
| Sonnet 5.5 | $0.00016 | $0.00764 |
| Haiku 4.5 | $0.00008 | $0.00382 |
Grade A, and why
image-prompting 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 4d 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.
- **Response shape:** `result.data[0].url` is either an HTTPS URL or a `data:image/...;base64,...` string. Save via `urllib.request.urlretrieve` for URLs or `base64.b64decode(item.b64_json)` for b64 payloads. How it starts
The opening of the file, as written. The whole thing — 318 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Image Prompting
Most image failures are prompt failures. This skill gives the MCP agent a repeatable structure for turning any user request into a prompt that renders clean typography, preserves layout on edits, and avoids AI slop. Defaults are tuned for GPT Image 2 (best legible text), with fallbacks for Nano Banana, Grok Imagine, and CogView.
Quick Decision Table
Prices: per image, and they change — look the model up live rather than trusting a number here: GET https://blockrun.ai/api/v1/models (Solana: https://sol.blockrun.ai/api/v1/models), find the entry whose id is the model below, and read pricing.per_image plus pricing.transaction_fee. That is the base-size rate; the exact amount for your size and quality is quoted in the HTTP 402 challenge before anything is signed. Size is the biggest
lever: any dimension above 1024 moves GPT Image 2 to the large tier and roughly
doubles the price ($0.064 → $0.127). Ask for 1536x1024 only when you need it.
| User wants... | Model | Mode | Size |
|---|---|---|---|
| Poster / typography-heavy asset | openai/gpt-image-2 |
generate | 1536x1024 or 1024x1536 |
| Clean product / UI mockup | openai/gpt-image-2 |
generate | 1024x1024 |
| Photoreal / fashion / editorial | openai/gpt-image-2 or google/nano-banana-pro |
generate | 1024x1024 |
| Pro-level photoreal at Flash speed | google/nano-banana-2 |
generate | 1024x1024 (only size) |
| Artistic / stylized / fast | google/nano-banana |
generate | 1024x1024 |
| Cheapest usable draft | zai/cogview-4 |
generate | 1024x1024 |
| Widescreen / banner on a budget | bytedance/seedream-5-pro |
generate | 2048x1024 or 1280x720 |
| Premium render or high-precision edit | openai/gpt-image-2.5-sunburst (-flare generates only, same price) |
generate or edit | 1024x1024 |
| Stylized Grok render, one step above the base | xai/grok-imagine-image-2.0 |
generate | 1024x1024 (only size) |
| Edit an existing image (localized change) | openai/gpt-image-2 |
edit | match source |
| Composite from multiple refs | openai/gpt-image-2 |
edit (multi-ref) | match target |
What ships with it
1 file 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.
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.
- 4d ago Changed · +2 lines 7875145c401f
- 1mo ago First seen · 316 lines · 79 tokens per session scan A 5dd8c3b78e08
image-prompting is a skill published in the GitHub repository BlockRunAI/blockrun-mcp (392 stars, last pushed 4d ago), licensed MIT. It adds 79 tokens to every session and 3,820 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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