content-radar

content-radar is a skill for Claude Code, Codex from TheMattBerman/openclaw-100k-posts-kit. It costs 102 tokens per session (1,803 once invoked), scanned A, original, MIT.

A research skill that combines performance signals, such as views and shares, with discussion signals from Reddit and X to create a niche briefing.

In plain words
What is it for?
Use it to find validated topics, early trends, and overlooked formats for content planning, using Virlo data and either automatic or agent-completed discussion searches.
Why use it?
Looking at only popular content or only audience discussions can miss opportunities. Combining them shows what is performing, being discussed, or emerging early.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: built for openclaw.

Good fit Use it to find validated topics, early trends, and overlooked formats for content planning, using Virlo data and either automatic or agent-completed discussion searches.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/themattberman/openclaw-100k-posts-kit/content-radar
Install

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.

Any agent
npx skills add TheMattBerman/openclaw-100k-posts-kit --skill content-radar
Clone the repo
git clone --depth 1 https://github.com/TheMattBerman/openclaw-100k-posts-kit

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for content-radar

README.md
[![agentmods](https://agentmods.dev/badge/skills/themattberman/openclaw-100k-posts-kit/content-radar/github.svg)](https://agentmods.dev/skills/themattberman/openclaw-100k-posts-kit/content-radar)
Your own site
<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/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.

agentmods 80×15 button for content-radar

Your own site · 80×15
<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="Reviewed on agentmods" width="80" height="20"></a>
Per session 102 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,803 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00102 $0.01803
Opus 5.5 $0.00041 $0.00721
Sonnet 5.5 $0.00020 $0.00361
Haiku 4.5 $0.00010 $0.00180

Measured 2mo ago against content hash 3098ed8089ee, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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 2mo ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/content-radar.sh), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/content-radar/SKILL.md · 190 lines

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 last30days is 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.

Read the full file on GitHub · 190 lines

Files

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.

Changes

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.

  1. 2mo ago First seen · 190 lines · 102 tokens per session scan A 3098ed8089ee

Subscribe to this mod's changes

content-radar is a skill published in the GitHub repository TheMattBerman/openclaw-100k-posts-kit (19 stars, last pushed 7mo ago), licensed MIT. It adds 102 tokens to every session and 1,803 once invoked, about $0.0004 per session on Opus 5.5. 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.

Related

content-radar compared with skills from other repositories

content-radar next to 6 skills from other repositories
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content-radarTheMattBerman/openclaw-100k-posts-kitSkill197mo agoMITA102Claude Code, Codex
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