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/content-radarnpx skills add TheMattBerman/openclaw-100k-posts-kit --skill content-radargit 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/content-radar)<a href="https://agentmods.dev/skills/themattberman/openclaw-100k-posts-kit/content-radar"><img src="https://agentmods.dev/badge/skills/themattberman/openclaw-100k-posts-kit/content-radar.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 | $0.00102 | $0.01803 |
| Opus 5 | $0.00051 | $0.00901 |
| Sonnet 5 | $0.00020 | $0.00361 |
| Haiku 4.5 | $0.00010 | $0.00180 |
Grade A, and why
content-radar 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 5d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Content Radar -- Signal Fusion Briefing System
Content Radar is the signal fusion and briefing layer in the pipeline.
Most content research only looks at one signal. You check what's trending on TikTok, or you ask Reddit what people are talking about. But neither alone tells the full story.
Content Radar fuses two signal types:
- Performance Signal (Virlo): What is actually getting views, shares, and reach right now. Real engagement data from TikTok, Instagram, and YouTube. No guessing.
- Discussion Signal (Reddit + X): What your audience is actively asking about, debating, and searching for. If
last30daysis installed, this can be pulled automatically. Otherwise the skill emits search directives for the agent to complete.
The magic is in the overlap. When something is BOTH performing AND being discussed, that is a validated content opportunity. When something is performing but NOT being discussed yet, you found an early signal. When something is being discussed but NOT performing yet, you found an untapped format opportunity.
Pipeline Role
Think of the stack like this:
- Virlo = raw performance signal
- Content Radar = signal fusion + niche briefing
- The Forge = brand-native concept generation
- Monday Drop = orchestrated weekly output
Content Radar does NOT replace Virlo. It uses Virlo as one input, adds discussion signal, then tells you what matters and why.
When To Use This Skill
Use Content Radar when you need the briefing and synthesis layer.
- Weekly content planning sessions
- Before building out a content calendar
- Before using The Forge skill, output feeds directly in
- Competitive research on a new niche
- Validating a content angle before investing in production
- Deciding what matters and why, not just what is performing
- Finding overlap, early signals, and format gaps
If you only want raw performance data, top videos, outliers, or comet management, use Virlo instead.
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.
- 5d ago First seen · 190 lines · 102 tokens per session scan A 3098ed8089ee
content-radar is a skill published in the GitHub repository TheMattBerman/openclaw-100k-posts-kit (20 stars, last pushed 5mo ago), licensed MIT. It adds 102 tokens to every session and 1,803 once invoked, about $0.0005 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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