Borrowing it
Nothing to install: this file belongs to Sma1lboy/rove. 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/Sma1lboy/rove/main/.claude/skills/general-video/SKILL.mdgit clone --depth 1 https://github.com/Sma1lboy/roveWrote 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/sma1lboy/rove/general-video)<a href="https://agentmods.dev/skills/sma1lboy/rove/general-video"><img src="https://agentmods.dev/badge/skills/sma1lboy/rove/general-video/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/sma1lboy/rove/general-video"><img src="https://agentmods.dev/badge/skills/sma1lboy/rove/general-video.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 5 findings, 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 Prompt Injection · line 91 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 98 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium Prompt Injection · line 100 Large whitespace padding was detected (a block of blank lines or a long run of spaces). This can push injected instructions below or to the right of the visible area so a human reviewer never sees them while the agent still reads them. Manual review of the hidden content is recommended.Fix: Remove the large whitespace padding (blank-line blocks or long space runs) and review any content hidden below or to the right of it. Keep skill files compact and reviewable so no instructions can be
- medium MCP Rug Pull · line 104 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]
- medium MCP Rug Pull · line 106 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 | $0.00114 | $0.02768 |
| Opus 5 | $0.00057 | $0.01384 |
| Sonnet 5 | $0.00023 | $0.00554 |
| Haiku 4.5 | $0.00011 | $0.00277 |
Grade A, and why
general-video 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 9d 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 — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.
general-video — general video workflow
Confirm the route before you build. This is the fallback for custom composition authoring. If the input clearly fits a specialized workflow, prefer it: topic explainer →
/faceless-explainer; GitHub PR →/pr-to-video; existing footage →/embedded-captions·/talking-head-recut; short unnarrated motion graphic →/motion-graphics. Out of scope: live / at-render-time data, NLE-style editing of a finished video, or producing footage HyperFrames can't capture. Unsure? Read/hyperframesfirst.
Build exactly what was asked. A title card is a title card — not a title card + three supporting scenes + captions. If extra scenes or elements would genuinely improve the piece, propose them; don't add them silently. For small edits (fix a color, adjust one duration, add one element), skip the planning steps and go straight to the build.
Approach
Discovery — open-ended requests only
For vague, exploratory requests ("make something for our brand", "a cool intro") — understand intent before picking colors:
- Audience — who watches? developers / executives / general consumers?
- Platform — where does it play? social (15s) / website hero / product demo / internal?
- Priority — what matters most? motion quality / content accuracy / brand fidelity / speed?
- Variations — one best shot, or 2-3 meaningfully different options (different pacing, energy, or structure — not just color swaps)?
For specific requests ("add a title card", "fix the timing on scene 3"), skip discovery.
Step 1 — Design system → hyperframes-design
Establish the visual identity first. If the project has a design spec, read it (precedence frame.md → design.md → DESIGN.md; treat it as brand truth — exact colors, fonts, constraints).
If no spec exists, you MUST read BOTH hyperframes-design/references/house-style.md AND hyperframes-design/references/video-composition.md before choosing any color or font. house-style.md gives the "interpret the prompt / generate real content" opener, lazy-default list, and layer recipe; video-composition.md gives the video-medium density / scale / foreground detailing (data bars, registration marks, monospace metadata, "8-10 elements, two the user didn't ask for") that separates "produced" from "generated." Reading only one is the most common miss — video-composition.md is the one agents skip, and it is exactly the one that prevents flat, centered, web-page-looking output. Do not self-invent a palette and skip these; crossing into hyperframes-design is mandatory here, not an optional branch. From there, also pull a named style/mood → references/visual-styles.md as needed. The spec/style defines the brand, not the composition rules.
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.
- 9d ago First seen · 111 lines · 114 tokens per session scan A fda88f092b0d
general-video is a skill published in the GitHub repository Sma1lboy/rove (122 stars, last pushed today), licensed MIT. It adds 114 tokens to every session and 2,768 once invoked, about $0.0006 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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