Market listener text.detect_problem_signal classifier
Scanned 9/11/2026
Install to Claude Code
npx -y skills add ponybunny-ai/ponybunny --skill text-detect-problem-signal --agent claude-codeInstalls into .claude/skills of the current project.
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---
name: text-detect-problem-signal
description: Market listener text.detect_problem_signal classifier
version: 1.0.0
author: PonyBunny
tags: [market-listener, classification, problem-detection]
phases: [execution]
user-invocable: false
disable-model-invocation: false
---
# Skill — text.detect_problem_signal
## Intent
Classify whether a piece of text contains a user-expressed problem, pain, or need.
## Inputs
```yaml
detect_request:
raw_text: string
platform: string
```
## Outputs
```yaml
detect_result:
has_problem_signal: boolean
signal_markers: string[]
label: enum [problem, how_to, bug, request, complaint, discussion, showcase, other]
confidence: number
```
## Tools
- llm.classify
## Policy
- Return ONLY valid JSON.
- Never provide advice or solutions.
- signal_markers must be verbatim snippets (no paraphrase).
- If uncertain, return best guess with low confidence.
## Failure Modes
- Invalid JSON: caller falls back to heuristic detection.
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Ultra-compressed communication mode. Cuts token usage ~75% by speaking like caveman while keeping full technical accuracy. Supports intensity levels: lite, full (default), ultra, wenyan-lite, wenyan-full, wenyan-ultra. Use when user says "caveman mode", "talk like caveman", "use caveman", "less tokens", "be brief", or invokes /caveman. Also auto-triggers when token efficiency is requested.