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 agentmods add skills/themattberman/openclaw-100k-posts-kit/virlonpx skills add TheMattBerman/openclaw-100k-posts-kit --skill virlogit clone --depth 1 https://github.com/TheMattBerman/openclaw-100k-posts-kitWrote 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/themattberman/openclaw-100k-posts-kit/virlo)<a href="https://agentmods.dev/skills/themattberman/openclaw-100k-posts-kit/virlo"><img src="https://agentmods.dev/badge/skills/themattberman/openclaw-100k-posts-kit/virlo.svg" alt="Measured on agentmods" 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 | $0.00110 | $0.01452 |
| Opus 5 | $0.00055 | $0.00726 |
| Sonnet 5 | $0.00022 | $0.00290 |
| Haiku 4.5 | $0.00011 | $0.00145 |
Grade A, and why
virlo 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 — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Virlo — Raw Performance Signal
What Is Virlo?
Virlo is the raw performance signal layer in the pipeline.
It scans TikTok, Instagram, and YouTube for niche content based on your keywords. It runs on a schedule (daily, weekly, etc.) and surfaces:
- Videos matching your keywords, filtered by platform, views, and date
- Creator Outliers — creators whose content is massively outperforming their typical reach (breakout signals)
- Meta Ads — ads related to your keywords (when enabled)
Think of it as a raw performance scanner for any niche. Set it once, and it continuously collects intelligence.
When To Use This Skill
Use Virlo when you need raw performance intelligence, not the final interpretation.
- What is performing right now?
- Show me top videos in this niche
- Show me breakout creators / outliers
- Pull raw Virlo data
- Show me ads tied to this niche
- Set up or manage a comet
Do NOT use Virlo when the real goal is:
- combining performance with Reddit/X discussion
- deciding what matters and why
- generating a weekly niche briefing
- feeding a fused signal set into The Forge
For those, use Content Radar.
Concepts
Comet (Custom Niche Config)
A "Comet" is Virlo's name for a saved niche configuration. You define:
- Name — your label for this tracking job
- Keywords — up to 20 phrases to scan for
- Platforms — tiktok, instagram, youtube (or all three)
- Cadence — how often to scrape (daily/weekly/monthly or cron)
- Min Views — filter out low-traction content
- Time Range — today, this_week, this_month, this_year
Once created, Virlo runs it automatically on your schedule and stores the results.
Creator Outliers
A creator is an "outlier" when one of their videos dramatically outperforms their baseline. The outlier ratio = viral views ÷ average views. Higher ratio = bigger breakout signal.
Pipeline Role
Think of the stack like this:
- Virlo = raw performance signal
- Content Radar = performance + discussion fused into a briefing
- The Forge = turns the briefing into brand-native concepts
- Monday Drop = orchestrates the weekly pack
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.
- 6d ago First seen · 174 lines · 110 tokens per session scan A 20f5eea61bba
virlo is a skill published in the GitHub repository TheMattBerman/openclaw-100k-posts-kit (20 stars, last pushed 5mo ago), licensed MIT. It adds 110 tokens to every session and 1,452 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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