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Review Mining · mkurman | DecimalAI

researchby mkurman

Review Mining

mkurman/review-mining

Source mkurman/zorai ↗License MIT

When the user wants to research customer pain points, complaints, or sentiment using review platforms like Trustpilot, G2, Capterra, or app stores. Also use when the user mentions "what are users saying", "competitor reviews", "pain points", or "voice of customer research".

SkillScore82Maintained

Automatic

Marketing & Content pack

Last verified 8/21/2026

What it changes

Passed 18 of 22 test cases with the skill, and 13 of 22 without it.

Without skill59%

With skill82%

Checks it passed that the model alone missed

Captures verbatim user language describing switching triggers.
Extracts verbatim consumer phrases rather than high-level summaries.
Captures verbatim user terminology rather than summarizing complaints.

and 3 more in the full report

6 fixed12 passed either way3 still failing1 broke

Pass-rate lift: +23 pp
Tokens: +24%
Agent turns: 0%
Response time: -5%

Model gemini-3.6-flashMeasured 8/21/2026v118 of 22 cases passed with skill

Tokens, turns and time describe resource use, not a dollar price.

Use this skill

Save it into your project's skills folder. Claude Code picks it up in its next session.

curl -fsSL --create-dirs -o .claude/skills/mkurman-review-mining/SKILL.md https://app.decimal.ai/s/mkurman-review-mining/SKILL.md

Want it pinned and updatable? pip install "decimalai>=0.15", then decimalai skills add mkurman-review-mining, and start Claude Code with claude --plugin-dir "$(git rev-parse --show-toplevel)/.agents"

1 · One-time — install the CLI (docs ↗)

pip install "decimalai>=0.15"

2 · Get the skill — writes .agents/skills/mkurman-review-mining/ and pins it in .decimal/skills.lock

decimalai skills add mkurman-review-mining

No CLI? Get the same file — curl · raw file

curl -fsSL --create-dirs -o .claude/skills/mkurman-review-mining/SKILL.md https://app.decimal.ai/s/mkurman-review-mining/SKILL.md

Raw file: /s/mkurman-review-mining/SKILL.md ↗ · machine-readable summary at /s/mkurman-review-mining.json ↗

Safety checks: 3 of 3 passed

Code scan CleanIntent PassedContent Clean

See it in action

One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.

1 of 6

Prompt

I am evaluating market dissatisfaction with enterprise CRM software like HubSpot and Salesforce. Should I focus my mining primarily on Amazon and App Store reviews, or where should I look for authentic B2B SaaS buyer sentiment? I'd like a summary of complaints and recommended sources.

What was checked, without and with the skill
Checked	Without skill	With skill
Recommends B2B SaaS review platforms such as G2, Capterra, or TrustRadius.	Passed	Passed
Captures verbatim user terminology rather than summarizing complaints.	Missed	Passed

case-07 · gemini-3.6-flash · 8/21/2026 · answers are capped and redacted

What's inside

The instructions your model reads when the skill loads.

SKILL.md55 linessingle file

---|-----------|-----------|-------| | ... | ... | ... | ... |

Voice of Customer Swipe File

Words users use for the problem: [list of exact phrases] Words users use for the desired outcome: [list of exact phrases] Emotional language: [frustration words, relief words]

Positioning Opportunities

[Opportunity 1]: [what you can claim based on competitor weakness]
[Opportunity 2]: [underserved use case you can own]


## Frameworks & Best Practices

**Where to mine by product type:**
| Product Type | Best Sources |
|-------------|-------------|
| B2B SaaS | G2, Capterra, TrustRadius |
| B2C / Consumer | Trustpilot, App Store, Play Store |
| Developer Tools | Reddit, Hacker News, GitHub Issues |
| E-commerce / DTC | Trustpilot, Amazon reviews |
| Any | Twitter/X complaints, Reddit threads |

**Review analysis principles:**
- **1-2 star reviews** reveal deal-breakers and switching triggers
- **3 star reviews** reveal "good enough but frustrated" — the most persuadable users
- **4-5 star reviews** reveal what users truly value (defend these in your product)
- **Recent reviews** (last 6-12 months) matter more than old ones
- **Verified purchase/user** reviews carry more weight

**Verbatim language is the output.** The exact words users use to describe their pain are more valuable than your summary. These become headlines, email subject lines, ad copy, and landing page copy.

**Common mistakes:**
- Only reading negative reviews (you miss what users actually value)
- Summarizing instead of quoting (you lose the authentic language)
- Treating all complaints equally (frequency x severity matters)
- Ignoring the context of who's reviewing (enterprise vs SMB, power user vs casual)
- Mining once and never returning (do this quarterly)

Track record

Benchmark

18 / 22

test cases passed, vs 13 / 22 without

Adoption

Users: 0
Times used: 0

Safety and source details

SkillSafety

✓ 3 of 3 passed

Code scan15 of 15 checks clean

0 critical · 0 warning · 0 info — scanner v4 — 8/3/2026

View 15 scanner checks

live_secretremote_code_executionreverse_shelldata_exfiltrationssrf_metadataagent_snoopinganti_refusaldestructive_commandsobfuscated_unicodeunicode_homoglyphopaque_blobsuspicious_urltool_overreachtrigger_abuseprompt_injection_phrasing

IntentSafe

LLM judge · does the skill do what it claims

ContentClean

LLM judge · policy & harmful-content review

Source

Imported

mkurman / zorai

skills/nontechnical/startup-founder-skills/review-mining/SKILL.md

View on GitHub ↗

License MITImported 8/3/2026Version v1

Other skills for the same job

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deanpeters/voice-of-customer-minerMine public reviews, app stores, and forums for unmet needs, competitor weaknesses, and switching triggers — with quoted evidence. Use when you want customer voice without waiting on interviews.Close match+41 pp pass-rate lift

More skills from the same source and nearby in the registry, with their headline benchmark lift.