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.

3,891 stars

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

$curl -o ~/.claude/skills/bs-detector/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1477009639zw-blip/bs-detector/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/bs-detector/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How bs-detector Compares

Feature / Agentbs-detectorStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/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.

Related Guides

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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Content & Documentation