Review Insight Starter
Extract evidence-linked pains, objections, and buyer language from a small set of customer reviews.
Free
Works with the AI tools you already use
Claude Code
Cursor
Codex CLI
GitHub Copilot
Gemini CLI+20 moreClaude CodeCursorCodex CLIGitHub CopilotGemini CLI
OpenClaw
Manus
Grok+17 agentsReview Insight Starter
Example session with this skill installed
Analyze these reviews for a reporting tool. R1: "The PDF export saves me rebuilding slides, but setup was confusing." R2: "I like the client PDF. I still copy numbers manually." R3: "Setup was easy for me; I wish every number linked to its source." R4 repeats R1 exactly. Extract themes and three messaging hypotheses. Do not infer market prevalence.
- Read your context and instructions
- Compiled the review insight starter
Sample boundary
Four supplied entries contain three unique review texts. R4 repeats R1 and is excluded from independent-source counts. Independence of R1–R3 is not verified. No dates, ratings, or customer roles were supplied.
| Theme | Category | Supporting IDs | Unique texts | Interpretation |
|---|---|---|---|---|
| Client-ready PDF exports | Praised benefit | R1, R2 | 2 | Repeated positive signal in this sample |
| Manual reporting work | Pain | R1, R2 | 2 | R1 reduces slide rebuilding; R2 still copies numbers |
| Source-linked numbers | Desired outcome | R3 | 1 | Tentative traceability opportunity |
| Setup experience varies | Contradiction | R1, R3 | 2 | One confusing and one easy experience; do not average away the difference |
Exact buyer language
- “The PDF export saves me rebuilding slides” — R1.
- “I still copy numbers manually.” — R2.
- “I wish every number linked to its source.” — R3.
Messaging hypotheses
- Client-ready PDFs without rebuilding slides. Supported by R1–R2; verify export requirements before publishing.
Less manual number copying. Pain appears in R2, but the product solution is not evidenced. Treat this as a feature hypothesis, not a current benefit claim.
3.
Numbers you can trace to their source. Desired by R3; demonstrate real source linkage before using it as a promise.
Validation questions
- What made setup confusing for R1 and easy for R3?
- Which numbers are copied manually, and why?
- Who receives the PDF and what fields do they require?
Next step: Gather additional distinct reviews with context and test these hypotheses against counterexamples. These counts describe only this supplied sample, not market demand.
Connects securely to your tools. The creator never sees your data.
About this skill
Find useful signals in customer reviews
A free starter for turning a small review sample into a compact, traceable insight sheet. Each theme stays linked to its original source, so anecdotes are not presented as market trends.
What it delivers
- Pains, outcomes, objections, and praised benefits.
- A theme table with source IDs and sample counts.
- An exact buyer-language bank.
- Messaging hypotheses, proof gaps, and validation questions.
Limits
Provide actual reviews. This skill does not invent quotes, scrape private sources, infer demographics, estimate market size, or turn small-sample counts into prevalence claims.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
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- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
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