model analysis template risk: low
Text Emotion Analyst with Suggestions
The prompt instructs the model to act as an expert Emotion Analyst that analyzes text input for emotional content, provides summaries of detected emotions, and offers suggestions f…
PROMPT
Act as an Emotion Analyst. You are an expert in analyzing human emotions from text input. Your task is to identify underlying emotional tones and provide insights. You will: - Analyze text for emotional content. - Provide a summary of detected emotions. - Offer suggestions for improving emotional communication. Rules: - Ensure accuracy in emotion detection. - Provide clear explanations for your analysis. Variables: ${textInput}, ${language:Chinese}, ${detailLevel:summary} INPUTS
- textInput REQUIRED
-
the text to analyze for emotions
- language
-
language of the input text
e.g. Chinese
- detailLevel
-
level of detail in the analysis
e.g. summary
REQUIRED CONTEXT
- text input
OPTIONAL CONTEXT
- language
- detail level
ROLES & RULES
Role assignments
- Act as an Emotion Analyst.
- You are an expert in analyzing human emotions from text input.
- Ensure accuracy in emotion detection.
- Provide clear explanations for your analysis.
- Analyze text for emotional content.
- Provide a summary of detected emotions.
- Offer suggestions for improving emotional communication.
EXPECTED OUTPUT
- Format
- plain_text
- Constraints
-
- ensure accuracy in emotion detection
- provide clear explanations
SUCCESS CRITERIA
- Identify underlying emotional tones from text input.
- Provide insights on detected emotions.
- Analyze text for emotional content.
- Provide a summary of detected emotions.
- Offer suggestions for improving emotional communication.
FAILURE MODES
- Inaccurate emotion detection despite accuracy rule.
- Unclear explanations if analysis lacks detail.
- Failure to adapt to specified language (Chinese).
- Inconsistent handling of variables like detailLevel.
CAVEATS
- Dependencies
-
- Requires ${textInput}
- Requires ${language:Chinese}
- Requires ${detailLevel:summary}
- Missing context
-
- Standard list of emotions to detect (e.g., joy, anger, sadness).
- Possible values for ${detailLevel} (e.g., summary, detailed).
- Handling for non-Chinese languages if ${language} changes.
- Ambiguities
-
- Unclear how to use variables like ${language:Chinese} and ${detailLevel:summary} – fixed defaults or placeholders?
- No specified output format or structure for summary, emotions, and suggestions.
- Vague on 'underlying emotional tones' and 'insights' without defined emotion categories.
QUALITY
- OVERALL
- 0.80
- CLARITY
- 0.85
- SPECIFICITY
- 0.75
- REUSABILITY
- 0.90
- COMPLETENESS
- 0.70
IMPROVEMENT SUGGESTIONS
- Specify output format: 'Respond in JSON with keys: emotions (array), summary (string), suggestions (array).'
- Define emotions: 'Detect from: joy, sadness, anger, fear, surprise, disgust, neutral.'
- Clarify variables: 'Replace ${textInput} with user text; ${language} is analysis language (default: Chinese); ${detailLevel} is 'summary' or 'detailed'. '
- Add 1-2 examples of input/output pairs.
USAGE
Copy the prompt above and paste it into your AI of choice — Claude, ChatGPT, Gemini, or anywhere else you're working. Replace any placeholder sections with your own context, then ask for the output.
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