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-VideoStudio --skill stage-consistencygit clone --depth 1 https://github.com/Orkas-AI/Orkas-VideoStudioWrote 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-videostudio/stage-consistency)<a href="https://agentmods.dev/skills/orkas-ai/orkas-videostudio/stage-consistency"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-videostudio/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-videostudio/stage-consistency"><img src="https://agentmods.dev/badge/skills/orkas-ai/orkas-videostudio/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 | $0.00092 | $0.01544 |
| Opus 5.5 | $0.00037 | $0.00618 |
| Sonnet 5.5 | $0.00018 | $0.00309 |
| Haiku 4.5 | $0.00009 | $0.00154 |
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 1mo 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 — 82 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. Describe the outcome; the tools are ovs image for portraits (incl. reference-image editing), ovs video for image-to-video, ovs edit extract-frame to pull an anchor frame, and a long-document strategy (chunking + retrieval/RAG over the source) for long sources (or the equivalent MCP tools).
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, generate ONE front portrait (full-body, front view, plain background) from its static+dynamic features with ovs image. This is the anchor — never regenerate it. Derive side/back views by reference-image editing the front portrait (so all three views are the same person). 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.
- 1mo ago First seen · 82 lines · 92 tokens per session scan A 02fb2cbca405
stage-consistency is a skill published in the GitHub repository Orkas-AI/Orkas-VideoStudio (329 stars, last pushed today), licensed MIT. It adds 92 tokens to every session and 1,544 once invoked, about $0.0004 per session on Opus 5.5. 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
claude-real-video
Watch a video for the user. Use when the user shares a video URL (YouTube etc.) or local video file and wants it summarized, analyzed, or discussed — Claude can't ingest video directly, so this skill extracts scene-aware keyframes + transcript first, then reads those.
brain-ingest
The process for digesting a conversation, document, or research result, classifying it, and writing it down as brain content (a root-page update or a new/updated page) through the brain CLI.
issue-resolve
Use when an assessed gflow-cli issue (verdict CONFIRMED-BUG or LIKELY-BUG) has localized, verifiable scope and should be driven to a fix. Mutating and gated: it works in an isolated worktree, fixes test-first, and opens a DRAFT PR for human review. Built to run autonomously (hermes-ops) within a strict action envelope…
issue-assessment
Use when triaging a GitHub issue for gflow-cli — a reporter's bug claim, a freshly-filed issue, or deciding whether and how to act on one. Also use when an autonomous agent (hermes-ops) picks up a labelled issue. Read-only: produces a verdict, an end-to-end-verifiability judgment, and a reporter-facing reply. Does not…
live-verify
Two-part gate for gflow-cli feature/fix work. Part 1 (Pre-flight): use when starting work on a gflow-cli feature or fix — confirms the checkout reflects current develop before investing effort. Part 2 (Live-verify): use before claiming gflow-cli work done, especially anything touching a generation code path…
sonar
Check the SonarCloud quality gate for a PR (or the current branch) and drive it to zero. Reports GREEN, or the exact PR-scoped new issues/hotspots/coverage gaps to fix.