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 charlesrapp/pruna-mcp-server --skill claude-skillgit clone --depth 1 https://github.com/charlesrapp/pruna-mcp-serverWrote 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/charlesrapp/pruna-mcp-server/claude-skill)<a href="https://agentmods.dev/skills/charlesrapp/pruna-mcp-server/claude-skill"><img src="https://agentmods.dev/badge/skills/charlesrapp/pruna-mcp-server/claude-skill/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/charlesrapp/pruna-mcp-server/claude-skill"><img src="https://agentmods.dev/badge/skills/charlesrapp/pruna-mcp-server/claude-skill.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 | $0.00050 | $0.00680 |
| Opus 5.5 | $0.00020 | $0.00272 |
| Sonnet 5.5 | $0.00010 | $0.00136 |
| Haiku 4.5 | $0.00005 | $0.00068 |
Grade A, and why
pruna scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
Pruna AI — Image & Video Generation
Generate images, edit photos, upscale, and create videos directly from Claude Code using Pruna AI's ultra-fast inference API.
Setup
Ensure PRUNA_API_KEY is set:
# macOS Keychain
export PRUNA_API_KEY=$(security find-generic-password -a $USER -s PRUNA_API_KEY -w)
# Or set directly
export PRUNA_API_KEY="your-key"
The MCP server must be configured in .claude/settings.local.json:
{
"mcpServers": {
"pruna": {
"command": "uvx",
"args": ["pruna-mcp-server"],
"env": { "PRUNA_API_KEY": "${PRUNA_API_KEY}" }
}
}
}
Image Generation
Use generate_image with these guidelines:
Prompt structure: Subject + Style + Lighting + Composition + Quality modifiers
Aspect ratios:
1:1— social media, product photos16:9— blog headers, YouTube thumbnails9:16— stories, TikTok, mobile4:3— standard photos
Model selection:
p-image— default, fastest (~1.5s, $0.005)flux-dev— highest quality (~3s, $0.005)flux-2-klein-4b— cheapest drafts (~1s, $0.0001)
Always use English prompts. Use seed for reproducible results when iterating.
Image Editing
Use edit_image with 1-5 reference images + text instruction.
Be explicit about what to change AND what to preserve. Default aspect_ratio: "match_input_image".
Video Generation
Use generate_video with prompt structure: [Subject] + [Action] + [Camera] + [Style]
p-video— premium quality, supports image+audio input ($0.02-0.04/s)wan-t2v— text-to-video onlywan-i2v— animate a static image
Keep duration short (5s) for iterations. Use 720p for drafts, 1080p for final.
Upscaling
Use upscale_image with target 1-8 megapixels. Set enhance_realism=true for AI-generated images.
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.
- 2mo ago First seen · 73 lines · 50 tokens per session scan A 296348d311a3
pruna is a skill published in the GitHub repository charlesrapp/pruna-mcp-server (5 stars, last pushed 3mo ago), licensed MIT. It adds 50 tokens to every session and 680 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 2026-08-31.
pruna compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| prunacharlesrapp/pruna-mcp-server | Skill | 5 | 3mo ago | MIT | A | 50 | Claude Code |
| imagegenopenai/codex | Skill | 134k | today | Apache-2.0 | A | 113 | Codex |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | yesterday | MIT | A | 200 | Claude Code, Codex |
| playwright-climicrosoft/playwright | Skill | 100k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| browser-automationopenclaw/openclaw | Skill | 394k | today | MIT | A | 36 | Claude Code |
| systematic-debuggingobra/superpowers | Skill | 314k | 4d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |