bs-detector
Detects key claims in long messages and summarizes the real point. Uses NLP to find what someone is actually saying vs. what they want you to believe.
Best use case
bs-detector is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Detects key claims in long messages and summarizes the real point. Uses NLP to find what someone is actually saying vs. what they want you to believe.
Teams using bs-detector should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/bs-detector/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How bs-detector Compares
| Feature / Agent | bs-detector | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Detects key claims in long messages and summarizes the real point. Uses NLP to find what someone is actually saying vs. what they want you to believe.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# BS Detector — Find the Real Point Detects claims, identifies fluff, and extracts the actionable truth from long messages. ## Usage ```bash python3 detect.py --input message.txt python3 detect.py --text "Your long slack message here..." ``` ## Features - Claim extraction from long text - Fluff detection (filler, buzzwords, corporate speak) - Core point summarization - Sentiment analysis - Key numbers and facts highlighted ## Example Input: Long corporate email Output: "Core message: Deadline is Friday. Key ask: Approval by EOD Thursday."
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name: article-factory-wechat