Orkas is a desktop application for commanding a team of AI agents through one chat, with a commander model assigning work to specialist agents in parallel or in sequence. People use it to coordinate research, writing, presentations, and software tasks while keeping files on their computer. The catalogue includes skills for extending the agents available to Orkas.
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 Orkas-AI/Orkas --skill stage-consistencygit clone --depth 1 https://github.com/Orkas-AI/OrkasWrote 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/orkas-ai/orkas/stage-consistency)<a href="https://agentmods.dev/skills/orkas-ai/orkas/stage-consistency"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/stage-consistency/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/orkas-ai/orkas/stage-consistency"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas/stage-consistency.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 | $0.00003 | $0.01627 |
| Opus 5 | $0.00002 | $0.00813 |
| Sonnet 5 | $0.00001 | $0.00325 |
| Haiku 4.5 | $0.00000 | $0.00163 |
Grade A, and why
stage-consistency 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.
How it starts
The opening of the file, as written. The whole thing — 84 lines — stays where its author put it; the contents beside it link to each section on GitHub.
stage-consistency
How to keep characters, settings, and style consistent across many generated shots (and across scenes in a long story). This is the depth layer on top of the generation line: the generation line makes clips; this skill makes the SAME character look the same in every clip. Host-neutral — describe the outcome; use generic built-in capabilities for generation/retrieval (Orkas: generate_image, generate_video, kb_*) and VideoStudio skill scripts for media extraction (stage-edit edit_video --op extract_frame via bin/run-skill.cjs).
1. Character bible (extract once, lock the look)
From the script/idea, extract every recurring character into project/characters/bible.json. For each character separate:
- static features — the immutable visual identity: face, hair, body shape, ethnicity, age range. These NEVER change shot-to-shot.
- dynamic features — changeable: clothing, accessories, expression.
- a single canonical name (merge every alias/pronoun for the same person to one id).
{
"alice": {
"static": "early-20s East-Asian woman, oval face, long black hair, slim build",
"dynamic": "green linen dress, small gold earrings",
"portrait": { "front": "characters/alice_front.png", "side": "characters/alice_side.png", "back": "characters/alice_back.png" }
}
}
2. Portrait anchor (generate once, then LOCK)
For each character, plan ONE front portrait as its own signed media_kind:"image" EDL segment, then generate it with generate_image using that segment id. This is the anchor — never regenerate it. Any separately generated side/back view is another explicit Gate C segment; otherwise derive views without a new hosted generation. Save paths into the bible.
- Cameo (the user uploads a photo to BE a character): use that photo AS the front portrait — skip generation for that character. Everything downstream references it.
3. Storyboard with character binding
Decompose the script into shots. Each shot records:
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 · 84 lines · 3 tokens per session scan A 145e21aa4f04
stage-consistency is a skill published in the GitHub repository Orkas-AI/Orkas (1,848 stars, last pushed yesterday), licensed MIT. It adds 3 tokens to every session and 1,627 once invoked, about $0.0000 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.
Other skills, from other repositories
video-script-generator
Generates video scripts with hooks, structured sections, pacing, and call-to-actions optimized for engagement and retention.
infographic-builder
Turns textual content into structured infographic formats suitable for reports, presentations, and educational materials.
video-editing-planner
Suggests editing structure, scene cuts, transitions, and pacing for improved video content quality and engagement.
caption-subtitle-formatter
Formats captions and subtitles for readability, timing, and accessibility across videos.
recording
Capture screen recordings and screenshots on any registered computer (macOS, Windows, Linux, HarmonyOS) and manage the recording library.
deepchat-cli
Use DeepChat's bundled CLI control plane for model inference, image/video/speech generation, transcription, OCR, artifact inspection, public configuration, Skills, and MCP operations. Activate when a user asks to invoke DeepChat capabilities that are not already exposed as a more specific tool, compare models, run a…