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 nextgentrainingacademy88-max/open-generative-studio --skill ogs-generategit clone --depth 1 https://github.com/nextgentrainingacademy88-max/open-generative-studioWrote 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/nextgentrainingacademy88-max/open-generative-studio/ogs-generate)<a href="https://agentmods.dev/skills/nextgentrainingacademy88-max/open-generative-studio/ogs-generate"><img src="https://agentmods.dev/badge/skills/nextgentrainingacademy88-max/open-generative-studio/ogs-generate.svg" alt="Measured on agentmods" 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 | $0.00418 | $0.03115 |
| Opus 5 | $0.00209 | $0.01558 |
| Sonnet 5 | $0.00084 | $0.00623 |
| Haiku 4.5 | $0.00042 | $0.00312 |
Grade A, and why
ogs-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 6d 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 — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenGen Studio Generate
Submit image and video generations through OpenGen Studio's hosted MCP server. OpenGen Studio is a credit-wallet SaaS - the user never sees an upstream vendor name, a USD price, or a raw model provider slug; everything customer-facing is "OpenGen Studio credits" and, when real money is involved (topping up the wallet), Malaysian Ringgit (RM/MYR).
Step 0 - Connection
The OpenGen Studio MCP server lives at https://mcp.your-domain.com/mcp. Connecting is
one-click OAuth: the user adds that URL as a custom connector (claude.ai:
Settings -> Connectors -> Add; Claude Code: claude mcp add --transport http ogs https://mcp.your-domain.com/mcp) and signs in with their OpenGen Studio account
when the browser prompt appears - no key handling needed. (Advanced fallback
for scripts: an API key ogs_sk_... from the developer section at
your-domain.com/mcp, sent as a bearer token.) If a tool call fails with an auth
error, the sign-in expired or was revoked - ask the user to reconnect the
connector at your-domain.com/mcp. Never ask the user to paste keys or tokens
into chat.
UX rules
- No raw JSON, IDs-as-code, or tool jargon in chat. Turn a tool result
into one plain sentence. Don't say "calling generate_image" or paste the
{"id":...}object - just deliver the outcome. - Always state the credit cost. Every successful
generate_image/generate_videoresult includescredits_charged- say it in plain language ("that used 15 OpenGen Studio credits"). For a run whose price scales with duration/resolution/mode (any video model, or an image model you're unsure about), callestimate_pricebeforegenerate_videoso the user isn't surprised. Skip the pre-estimate only for the cheapest, flat-rate defaults (e.g. a quick Z Image or Nano Banana 2 image) - report the actual charge after the fact instead. - On an insufficient-credits failure, call
get_balanceto tell the user their exact balance, then point them tohttps://www.your-domain.com/walletto top up. Don't unilaterally downgrade to a cheaper model to dodge the shortfall unless the user asks for that. - Money is OpenGen Studio credits, full stop - never say "USD", "dollars", or an upstream vendor name (this is a hard product rule; the server itself scrubs vendor names out of error text, but keep your own language clean too). RM/MYR only comes up when discussing wallet top-ups, never per-generation cost.
- Deliver results as the media URL + one line, not the full tool response: model used, and duration/size if relevant. If the user needs a local file, tell them to save the URL - OpenGen Studio doesn't guarantee it lives forever.
- One question at a time. Don't front-load "which model, what aspect
ratio, how many reference images" all at once - pick sane defaults
(
nano-bananaisgenerate_image's own default) and ask only for what's genuinely missing (e.g.generate_videohas no default model, so ask if the user hasn't named one and the brief doesn't make it obvious). - Reference images must be public URLs.
image_urlsis validated as a URL by the tool - a local file path is rejected outright. If the user hands you a local file, tell them it needs to be hosted somewhere reachable first (their own upload, a public bucket, etc.) before you can pass it in.
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.
- 6d ago First seen · 181 lines · 418 tokens per session scan A fb4e2f67ca15
ogs-generate is a skill published in the GitHub repository nextgentrainingacademy88-max/open-generative-studio (0 stars, last pushed 13d ago), licensed MIT. It adds 418 tokens to every session and 3,115 once invoked, about $0.0021 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 2026-08-31.
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