stagewise is an open-source agentic IDE that combines a coding agent, browser-based app previews, debugging tools, and git workflows in one development environment. Developers use it to build and inspect applications with models from different providers. Catalogue add-ons extend the IDE's agent workflows.
Borrowing it
Nothing to install: this file belongs to stagewise-io/stagewise. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/stagewise-io/stagewise/main/.agents/skills/prompt-optimization/SKILL.mdgit clone --depth 1 https://github.com/stagewise-io/stagewiseWrote 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/stagewise-io/stagewise/prompt-optimization)<a href="https://agentmods.dev/skills/stagewise-io/stagewise/prompt-optimization"><img src="https://agentmods.dev/badge/skills/stagewise-io/stagewise/prompt-optimization/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/stagewise-io/stagewise/prompt-optimization"><img src="https://agentmods.dev/badge/skills/stagewise-io/stagewise/prompt-optimization.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 | $0.00104 | $0.00841 |
| Opus 5 | $0.00052 | $0.00420 |
| Sonnet 5 | $0.00021 | $0.00168 |
| Haiku 4.5 | $0.00010 | $0.00084 |
Grade A, and why
prompt-optimization 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 10d 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.
The source is not reproduced here
Licensed AGPL-3.0
The repository is licensed AGPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
7 files 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.
- 10d ago First seen · 66 lines · 104 tokens per session scan A 0070b32e0c34
prompt-optimization is a skill published in the GitHub repository stagewise-io/stagewise (6,809 stars, last pushed today), licensed AGPL-3.0. It adds 104 tokens to every session and 841 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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omh-llm-app-dev
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omh-model-setup
This is a Hermes-native model-setup workflow skill.
omh-model-optimization
This is a Hermes-native model-optimization workflow skill.
model-onboarding
Onboard a new model generation or sibling into oh-my-hermes: probe router recognition, research the official contract, write trait-to-counter calibration, place routing in both lanes, price from documented list only, gate machine config on a served route, prove with the gates, close with a benchmark pair. Use when a…