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 renalpelvisdeinocheirus70/ozor-skills --skill ozor-social-batchgit clone --depth 1 https://github.com/renalpelvisdeinocheirus70/ozor-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/renalpelvisdeinocheirus70/ozor-skills/ozor-social-batch)<a href="https://agentmods.dev/skills/renalpelvisdeinocheirus70/ozor-skills/ozor-social-batch"><img src="https://agentmods.dev/badge/skills/renalpelvisdeinocheirus70/ozor-skills/ozor-social-batch/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/renalpelvisdeinocheirus70/ozor-skills/ozor-social-batch"><img src="https://agentmods.dev/badge/skills/renalpelvisdeinocheirus70/ozor-skills/ozor-social-batch.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00133 | $0.02333 |
| Opus 5 | $0.00067 | $0.01167 |
| Sonnet 5 | $0.00027 | $0.00467 |
| Haiku 4.5 | $0.00013 | $0.00233 |
Grade A, and why
ozor-social-batch 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 12d 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.
This is a copy
100% identical to ozor-social-batch — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 210 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Ozor Social Batch Generator
Generate a coordinated set of social media video prompts for multiple platforms from a single input. Instead of creating one video and awkwardly resizing it, this skill produces platform-native prompts that respect each platform's format, duration, and audience conventions.
Supported Platforms
| Platform | Format | Duration | Style Notes |
|---|---|---|---|
| Instagram Reels | 9:16 portrait | 15–30s (max 90s) | Hook in first 1s, trending audio-friendly, bold text overlays |
| TikTok | 9:16 portrait | 15–60s | Fast-paced, text-heavy, casual tone, trend-aware |
| YouTube Shorts | 9:16 portrait | 15–60s | Clean, informative, can be slightly longer |
| LinkedIn Video | 16:9 landscape | 30–60s | Professional, value-driven, data-friendly |
| X (Twitter) Video | 16:9 landscape | 15–30s | Punchy, opinion-driven, conversation-starting |
| Facebook Reels | 9:16 portrait | 15–30s | Broad appeal, clear message, shareable |
| Pinterest Video Pin | 9:16 portrait (2:3 also works) | 15–30s | Aesthetic, inspirational, save-worthy |
Workflow
Phase 1 — Understand the Input
The user provides a topic, product, message, or existing content. Extract:
- Core message — the single thing every video must communicate
- Product/brand — what's being promoted
- Target audience — who this is for
- Goal — what the videos should achieve (awareness, clicks, sign-ups, engagement)
- Available platforms — which platforms the user wants (or recommend the best 3–4 if unspecified)
- Brand elements — colors, tone, visual style
- Assets — any images, screenshots, or logos available
Phase 2 — Plan the Batch
Create a batch plan showing what will be produced:
## Social Video Batch Plan
**Topic:** [core message]
**Brand:** [product/company]
**Platforms:** [list]
| # | Platform | Format | Duration | Angle |
|---|----------|--------|----------|-------|
| 1 | Instagram Reels | 9:16 | 15s | [hook-driven teaser] |
| 2 | TikTok | 9:16 | 30s | [trend-style explainer] |
| 3 | LinkedIn | 16:9 | 45s | [professional value prop] |
| 4 | YouTube Shorts | 9:16 | 30s | [informative how-to] |
What ships with it
1 file 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.
- 12d ago First seen · 210 lines · 133 tokens per session scan A 3767c4b900c6
ozor-social-batch is a skill published in the GitHub repository renalpelvisdeinocheirus70/ozor-skills (2 stars, last pushed 2d ago), licensed MIT. It adds 133 tokens to every session and 2,333 once invoked, about $0.0007 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to ozor-social-batch, differing in 0 lines, and is treated as a copy.
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