customer-research
Research customer problems, alternatives, triggers, objections, and language with traceable evidence that can change product or growth decisions.
Skill by luxiaolei
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/luxiaolei-customer-research
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: marketing, research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/customer-research
What's inside
- Skill name
customer-research- Description
- Research customer problems, alternatives, triggers, objections, and language with traceable evidence that can change product or growth decisions.
- License
- MIT
- Instructions
- 22 lines in SKILL.md · view on GitHub
Files (2)
- SKILL.md
- SKILL.zh-CN.md
SKILL.md (first lines)
# Customer Research Start from a decision, not an open-ended persona exercise. ## Evidence order Prefer first-party interviews/support/surveys/usage context when available; then direct public user discussions and reviews; then competitor/customer-facing material; use commentary and inferred personas only as lower-confidence context. ## Method 1. Define the decision: positioning, product priority, landing copy, channel, content question, pricing, or another concrete choice. 2. Segment by behavior, use case, urgency, constraints, and current alternative rather than demographics alone. 3. Capture problem language, trigger, desired outcome, current workaround, switching barrier, objections, proof required, and where the user seeks information. 4. Record source, date, population/context, quote versus inference, and confidence. 5. Look for convergence and contradictions. Do not turn a few vivid comments into market prevalence. 6. Translate evidence into testable implications for product, offer, message, content, channel, or onboarding. ## Deliver Return a small segment/problem map, evidence table, unresolved questions, rejected assumptions, and recommended experiments. Never present a synthetic persona or model inference as a customer fact.
From luxiaolei/AutoSpread, MIT.
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Sep 27, 2026 (1 month ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/luxiaolei/AutoSpread
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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SkillAFreshness: AClaude Code +9 - 0.561score
agent-readiness
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Make a website usable by user-triggered AI agents and machine clients without confusing agent operability with GEO ranking.
SkillAFreshness: AClaude Code +9 - 0.561score
paid-acquisition
luxiaolei
Run bounded paid acquisition experiments only when audience, offer, destination, attribution, budget, and stop rules are ready.
SkillAFreshness: AClaude Code +9 - 0.561score
channel-selection
luxiaolei
Choose a small channel portfolio based on audience behavior, product demonstration fit, intent, economics, and existing evidence.
SkillAFreshness: AClaude Code +9 - 0.561score
channel-operations
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Prepare, publish, schedule, and verify approved content through authorized APIs, CLIs, or UI automation while preserving external evidence.
SkillAFreshness: AClaude Code +9 - 0.561score
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Cite this page
customer-research skill. Agent Mart. https://agentmart.dev/skills/luxiaolei-customer-research (last updated 2026-10-24)