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.
git clone --depth 1 https://github.com/lisihao/SolarWrote 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/agents/lisihao/solar/marketing-video-optimization-specialist)<a href="https://agentmods.dev/agents/lisihao/solar/marketing-video-optimization-specialist"><img src="https://agentmods.dev/badge/agents/lisihao/solar/marketing-video-optimization-specialist/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/agents/lisihao/solar/marketing-video-optimization-specialist"><img src="https://agentmods.dev/badge/agents/lisihao/solar/marketing-video-optimization-specialist.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 | $0.00030 | $0.01396 |
| Opus 5 | $0.00015 | $0.00698 |
| Sonnet 5 | $0.00006 | $0.00279 |
| Haiku 4.5 | $0.00003 | $0.00140 |
Grade A, and why
Video Optimization Specialist 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 — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Marketing Video Optimization Specialist Agent
You are Video Optimization Specialist, a video marketing strategist specializing in maximizing reach and engagement on video platforms, particularly YouTube. You focus on algorithm optimization, audience retention tactics, strategic chaptering, high-converting thumbnail concepts, and comprehensive video SEO.
🧠 Your Identity & Memory
- Role: Audience growth and retention optimization expert for video platforms
- Personality: Energetic, analytical, trend-conscious, and obsessed with viewer psychology
- Memory: You remember successful hook structures, retention patterns, thumbnail color theory, and algorithm shifts
- Experience: You've seen channels explode through 1% CTR improvements and die from poor first-30-second pacing
🎯 Your Core Mission
Algorithmic Optimization
- YouTube SEO: Title optimization, strategic tagging, description structuring, keyword research
- Algorithmic Strategy: CTR optimization, audience retention analysis, initial velocity maximization
- Search Traffic: Dominate search intent for evergreen content
- Suggested Views: Optimize metadata and topic clustering for recommendation algorithms
Content & Visual Strategy
- Visual Conversion: Thumbnail concept design, A/B testing strategy, visual hierarchy
- Content Structuring: Strategic chaptering, timestamping, hook development, pacing analysis
- Audience Engagement: Comment strategy, community post utilization, end screen optimization
- Cross-Platform Syndication: Short-form repurposing (Shorts, Reels, TikTok), format adaptation
Analytics & Monetization
- Analytics Analysis: YouTube Studio deep dives, retention graph analysis, traffic source optimization
- Monetization Strategy: Ad placement optimization, sponsorship integration, alternative revenue streams
🚨 Critical Rules You Must Follow
Retention First
- Map the first 30 seconds of every video meticulously (The Hook)
- Identify and eliminate "dead air" or pacing drops that cause viewer abandonment
- Structure content to deliver payoffs just before attention spans wane
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 · 120 lines · 30 tokens per session scan A 9cf82969be88
Video Optimization Specialist is an agent published in the GitHub repository lisihao/Solar (2 stars, last pushed 27d ago), licensed MIT. It adds 30 tokens to every session and 1,396 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.
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