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 simota/agent-skills --skill stagegit clone --depth 1 https://github.com/simota/agent-skillsWrote 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/simota/agent-skills/stage)<a href="https://agentmods.dev/skills/simota/agent-skills/stage"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/stage/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/simota/agent-skills/stage"><img src="https://agentmods.dev/badge/skills/simota/agent-skills/stage.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, 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 MCP Rug Pull · line 174 npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.Fix: Pin the version: npx @scope/[email protected]
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 | $0.00038 | $0.03347 |
| Opus 5 | $0.00019 | $0.01673 |
| Sonnet 5 | $0.00008 | $0.00669 |
| Haiku 4.5 | $0.00004 | $0.00335 |
Grade A, and why
stage 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 — 215 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stage
Generate presentation slides through Markdown-based tools. Stage turns talk outlines, specifications, and learning materials into structured, visually coherent slide decks with speaker notes and timing guidance.
Trigger Guidance
Use Stage when the user needs:
- a slide deck generated from content or an outline
- presentation narrative structure designed (story arc, flow)
- Marp, reveal.js, or Slidev slide code
- speaker notes with timing cues
- a custom slide theme or layout
- conference talk or LT optimized slides
- code-heavy technical presentations
- slide export pipeline (PDF/HTML/PPTX)
Route elsewhere when the task is primarily:
- diagrams or charts without slide context:
Canvas - specification or design documents:
Scribe - document format conversion:
Scribe - UX writing or microcopy:
Prose - video scripts or storyboards:
Cue - learning document creation:
Tome
What ships with it
8 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.
- 6d ago First seen · 215 lines · 38 tokens per session scan A 914221ced014
stage is a skill published in the GitHub repository simota/agent-skills (76 stars, last pushed 7d ago), licensed MIT. It adds 38 tokens to every session and 3,347 once invoked, about $0.0002 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 2026-09-03.
Other skills, from other repositories
video-transcription
Transcribe video and audio files to SRT subtitles with speaker diarization using the Soniox (default) or AssemblyAI API. Use when the user wants to transcribe meetings, videos, or audio files. Supports MKV, MP4, MOV, M4A, MP3. Triggers on "/transcribe", "transcribe my meetings", "transcribe videos in /Movies", or any…
nano-banana-imagegen
Generate and edit images using Google Gemini image models via the nano-banana CLI. Use when the user asks to create, generate, make, or edit images with AI. Supports text-to-image, image editing, style transfer, and multi-image composition. Trigger on requests like "create an image", "generate a picture", "make me a…
veo-generator
Render a scripted video project into mp4 clips with the Google Veo 3.1 API. Reads a project's shot package (shots/.md), one clip per camera cut, reusing each shot's prompt and sketch — world anchor only with --with-reference, seed unless --no-seed. Use on "render the Veo video for ", "generate the videos from the shot…
veo-showreel-production-kit
Turn a video timeline + voiceover into a reproducible, sliceable Veo 3.1 prompt package with a consistency anchor and AI storyboard sketches.
creative-claude-design
Design one-off HTML artifacts (landing, deck, prototype).
taste-feedback
Use during the build phase to show the user intermediate visual output and ask for taste direction before the full build completes — enables mid-flight course correction so taste mismatches are caught early, not in review.