customer-research
customer-research is a User interviews & surveys skill for AI agents, published by coreyhaines31 in the marketingskills repository on GitHub. Skillspace rates customer-research D (66/100) and it passed the safety scan; a judge model has also reviewed it.
When the user wants to conduct, analyze, or synthesize customer research. Use when the user mentions "customer research," "ICP research," "talk to customers," "analyze transcripts," "customer interviews," "survey analysis," "support ticket analysis," "voice of customer," "VOC," "build personas," "customer personas," "jobs to be done," "JTBD," "what do customers say," "what are customers struggling with," "Reddit mining," "G2 reviews," "review mining," "digital watering holes," "community research," "forum research," "competitor reviews," "customer sentiment," "PMF survey," "product/market fit survey," "customer interview questions," "interview outreach," "Sales Safari," or "find out why customers churn/convert/buy." Use for analyzing existing research assets, mining online sources, AND running primary research (interviews and surveys). For writing copy informed by research, see copywriting. For acting on research to improve pages, see cro.
- Grade
- D
- Quality
- 66 / 100
- Safety
- Passed
- GitHub stars
- 49,936
Placed #3 of 6 in the judged category final for User interviews & surveys.
This rating describes the version of the repository we crawled; it may have changed since, so go by its current files.
Our review
- Architecture
- 96 / 100
- Maturity
- Basic: a single SKILL.md
- Security scan
- No issues found
- License
- Not declared. Check the repository before reusing it.
Judge review
Placed #3 of 6 in the judged category final for User interviews & surveys.
- Trigger
88 88 - Instructions
93 93 - Specificity
92 92 - Safety
85 85 - Disclosure
68 68 - Maintenance
45 45
Exceptionally thorough three-mode research methodology with an evidence-based High/Medium/Low confidence framework and explicit recency and bias guardrails.
Not checked yet
- Category is a classifier prediction; no model has read this skill yet
- No blind task eval yet
- Scope (portable / vendor / repo-internal) not assessed; only the top of each category is read for scope
- Sibling files (scripts, references) not fetched; security scan covers SKILL.md only
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