Mira — Text & Sentiment Analyst AI Skill
$29.00
Sale price
$29.00
Regular price
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Mira — Text & Sentiment Analyst AI Skill
$29.00
Sale price
$29.00
Regular price
⚡ Instant download
◆ Claude & ChatGPT
∞ Keep forever
Instant download · 30-day money-back guarantee. Pay once, keep forever — no subscription. Refund policy
Turn reviews, transcripts, and feedback into evidence-cited themes and sentiment — no NLP needed.
- Sentiment by topic and intensity, not one blunt score
- Thematic coding via Braun and Clarke methodology
- Every finding backed by 3-5 examples from the text
- What's absent from the data flagged, not just present
Researchers, CX teams, and analysts working with qualitative text.A qual research analyst runs $150+/hr — this is one file, yours forever.
// what's inside
Drop Mira into Claude and get a Text & Sentiment Analyst who identifies themes, codes qualitative data, assesses sentiment by topic and intensity, analyses customer reviews, processes interview transcripts, and backs every finding with specific examples from the text — without requiring you to know NLP or Python.
Text data is rarely uniformly positive or negative — customers who love the product but hate the delivery, employees who value colleagues but dislike management. Mira is one of the most evidence-cited AI text analysis tools available in Claude format — she never asserts a theme or sentiment without showing where in the data it comes from. Every claim requires 3–5 specific examples from the source text. She explains the analytical methodology used (thematic analysis, sentiment scoring, content analysis) so findings are understood rather than just accepted, and she identifies what is absent from a text as clearly as what is present.
What you get
- → Sentiment analysis with examples — overall positive, negative, neutral, and mixed sentiment assessment, sentiment by topic and theme within a document, intensity rating (strongly negative vs mildly negative), emotional tone identification (anger, satisfaction, frustration, delight), and customer review sentiment broken down by product, service, or attribute
- → Thematic analysis — recurring themes identified and systematically coded using Braun & Clarke methodology, theme hierarchies built (themes and sub-themes), prominence and frequency assessed, and a priori vs emergent coding applied depending on whether the analytical framework is pre-existing or generated from the data
- → Qualitative research data analysis — interview and focus group transcript analysis, thematic coding across multiple interviews, pattern identification, key findings synthesised in structured write-up format, and qualitative research findings presented as evidence-cited, publishable-quality analysis
- → Customer and employee feedback analysis — NPS open-ended comment analysis, CSAT verbatim breakdowns, employee survey open-ended response analysis, social media comment sentiment, and customer review theme identification with specific quotes supporting each finding
- → Content and discourse analysis — key term and phrase frequency analysis, topic framing identification (how a subject is presented, not just what is said), persuasive and rhetorical technique identification, brand language and tone analysis, and what is absent from a text as well as what is present
- → Applied text analysis across industries — media and press coverage analysis, political and policy language analysis, contract and legal language review, competitive communications analysis, and analytical framework and sampling strategy design for large datasets that exceed what can be processed directly in a single session
📄 mira-text-analyst.skill
Under 2 min install
Works with Claude, ChatGPT & any AI chat
How to install
Download the .skill package → open Claude → paste SKILL.md into your Project Instructions or system prompt → paste the text, reviews, transcripts, or feedback you need analysed → Mira identifies themes, assesses sentiment, and produces evidence-cited findings instantly. Paste the content directly — for very large datasets she designs the analytical framework and sampling approach.
# Mira — Text & Sentiment Analyst AI Skill You are Mira, a text and sentiment analyst. No theme asserted without showing where it comes from. ## What you do - Sentiment analysis by topic and intensity with examples - Thematic coding and qualitative transcript analysis - Content and discourse analysis across industries ## How you work 1. Cite 3-5 specific examples for every claim 2. Name the methodology so findings are understood 3. Flag what's absent as clearly as what's present
Excerpt from the actual file you'll download.
// try it
$Analyse these 200 customer reviews for themes and sentiment by topic.
Mira returns: sentiment broken down by topic and intensity, not one overall score → themes coded with Braun & Clarke methodology into themes and sub-themes → 3-5 specific quotes backing every finding → a note on what's absent from the text plus the methodology used, so findings are understood not just accepted.
// how to install
Under 2 minutes
Four steps. Any AI chat.
- 01Download the file
After checkout, the download link lands in your inbox. Save the file anywhere on your device.
- 02Open your AI chat
Claude, ChatGPT, Gemini, Grok, or Copilot — whichever one you already use.
- 03Paste the file contents
Drop it into the system prompt, Project instructions, or custom instructions field.
- 04Start working
Your AI is now configured as a specialist. Ask it anything inside its domain.
No technical knowledge required. No subscription. Pay once, keep forever.
// compatible with
Works with every major AI chat.
Drop the file into your AI's system prompt, Project instructions, or custom instructions. No setup. No code. No vendor lock-in.
- Claude
- ChatGPT
- Gemini
- Grok
- Copilot
Works with any AI chat that accepts a system prompt or custom instructions.
Ready to specialise your AI?
One drop-in file. Pay once, keep forever — works with Claude & ChatGPT.
// faq