OpenClacky is an open-source AI coding agent that uses OpenAI-compatible models to perform tasks through tools and subagents. It is intended for developers who want an agent with flexible model choice and lower token usage. The catalogue skills and agents extend its workflows and capabilities.
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 clacky-ai/openclacky --skill media-gengit clone --depth 1 https://github.com/clacky-ai/openclackyWrote 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/clacky-ai/openclacky/media-gen)<a href="https://agentmods.dev/skills/clacky-ai/openclacky/media-gen"><img src="https://agentmods.dev/badge/skills/clacky-ai/openclacky/media-gen/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/clacky-ai/openclacky/media-gen"><img src="https://agentmods.dev/badge/skills/clacky-ai/openclacky/media-gen.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 6 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 Data Exfiltration · line 25 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 32 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 91 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 280 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 389 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
- medium Data Exfiltration · line 501 Data is being sent to an external URL. This could be legitimate telemetry or data exfiltration. Manual review is recommended.Fix: Verify the destination URL is trusted and necessary. Remove or replace with documented APIs. Ensure no secrets, tokens, or PII are transmitted.
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 | $0.00148 | $0.07303 |
| Opus 5 | $0.00074 | $0.03651 |
| Sonnet 5 | $0.00030 | $0.01461 |
| Haiku 4.5 | $0.00015 | $0.00730 |
Grade B, and why
media-gen scanned grade B with 2 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
`curl --data @file`. **Do NOT inline the base64 into `-d "{…}"`** — a frame's Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s http://${CLACKY_SERVER_HOST}:${CLACKY_SERVER_PORT}/api/media/types How it starts
The opening of the file, as written. The whole thing — 568 lines — stays where its author put it; the contents beside it link to each section on GitHub.
media-gen
Generate and edit images on demand by calling the local Clacky HTTP server, which dispatches to whichever image-generation model the user configured (type=image in their model settings). Editing (image-in → image-out) works with any image model that accepts image input — most current ones do.
Endpoint
POST http://${CLACKY_SERVER_HOST}:${CLACKY_SERVER_PORT}/api/media/image
GET http://${CLACKY_SERVER_HOST}:${CLACKY_SERVER_PORT}/api/media/types
Step 1 — Verify a backend is configured
Before generating anything, confirm the user has a type=image model set up:
curl -s http://${CLACKY_SERVER_HOST}:${CLACKY_SERVER_PORT}/api/media/types
If the response shows image.configured = false, stop and tell the user:
还没有配置生图模型。请打开设置页 → 添加模型 → 类型选
image（走 openclacky 官方网关时推荐or-gemini-3-pro-image或or-gpt-image-2）。配好后再让我生图。
Do NOT try to fall back to terminal + a hand-written curl https://api.openai.com/... — that bypasses the user's configured backend and won't be billed correctly.
You do NOT configure models — the user does, in the settings page. Never
edit the user's config.yml to add or change a model, and never invent a model
name from memory (e.g. or-gpt-5.4-image-2 does not exist). The real, current
model is whatever /api/media/types reports under image.model. If you think a
different model is needed, tell the user which one to set in the settings page —
don't touch the config file yourself.
Step 2 — Generate the image
The model does NOT honor exact pixel sizes
There is no size / width / height field — the only shape control is
aspect_ratio (landscape / square / portrait), and even that is just a
rough hint (ask for 576x96 and you may get 1408x768). When the user needs an
exact pixel size, a grid, an icon at NxN, or a spritesheet, generate first at
whatever size the model gives, then resize / crop / tile to the exact pixels with
ImageMagick (magick). Verify with magick identify before reporting done.
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.
- 11d ago First seen · 568 lines · 148 tokens per session scan B 59bee7b619be
media-gen is a skill published in the GitHub repository clacky-ai/openclacky (1,188 stars, last pushed today), licensed MIT. It adds 148 tokens to every session and 7,303 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it B with 2 findings (sends data to an external url, 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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A guide for turning character, scene, and prop ideas into prompts for generating consistent reference images. It covers layouts, camera views, visual identity, and continuity across image variations.