Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add brainbytes-dev/everything-claude-marketing --skill customer-interviewsgit clone --depth 1 https://github.com/brainbytes-dev/everything-claude-marketingWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/customer-interviews)<a href="https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/customer-interviews"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/customer-interviews/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/brainbytes-dev/everything-claude-marketing/customer-interviews"><img src="https://agentmods.dev/badge/skills/brainbytes-dev/everything-claude-marketing/customer-interviews.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.03342 |
| Opus 5.5 | $0.00012 | $0.01337 |
| Sonnet 5.5 | $0.00006 | $0.00668 |
| Haiku 4.5 | $0.00003 | $0.00334 |
Grade A, and why
customer-interviews scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 289 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customer Interviews
When to Activate
Use this skill when building or refining buyer personas, gathering voice-of-customer (VoC) data for messaging, understanding why customers buy (or don't), conducting Jobs-to-be-Done research, developing case studies, improving onboarding or retention, validating product or market assumptions, or when someone asks you to "talk to customers" or "gather qualitative insights." Interviews are the highest-signal research method in marketing when done well.
First Questions
Before planning interviews, clarify:
- What is the research objective? (persona development, messaging, churn analysis, product feedback, journey mapping)
- Who should we interview? (current customers, churned customers, prospects who didn't buy, target audience who doesn't know us)
- How many interviews? (8-15 for pattern recognition; 5 for quick directional insight)
- What format? (video call, phone, in-person — video is the default for remote)
- What will we do with the findings? (personas, messaging doc, product roadmap input, content strategy)
- What do we already believe? (document assumptions before interviews so you can test them)
Core Rules
- Listen more than you talk. The ideal ratio is 80/20 — the interviewee talks 80% of the time. Your job is to ask questions and then shut up.
- Never lead the witness. Ask open-ended questions. Never suggest the answer you're hoping for. "What was that experience like?" beats "Was that frustrating?"
- Follow the energy. When someone's voice changes, they lean in, or they start a story unprompted — that's where the gold is. Follow it with probing questions.
- Seek stories, not opinions. "Tell me about the last time you..." yields better data than "What do you think about...?" Past behavior is more reliable than hypothetical preferences.
- Uncomfortable pauses are your friend. When you stop talking, people fill the silence with their real thoughts. Don't rush to the next question.
- One interview is an anecdote. Five interviews are a pattern. Don't over-index on a single conversation. Wait for themes to emerge across multiple interviews.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2mo ago First seen · 289 lines · 30 tokens per session scan A 6137770bd904
customer-interviews is a skill published in the GitHub repository brainbytes-dev/everything-claude-marketing (10 stars, last pushed 7mo ago), licensed MIT. It adds 30 tokens to every session and 3,342 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
customer-interviews compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| customer-interviewsbrainbytes-dev/everything-claude-marketing | Skill | 10 | 7mo ago | MIT | A | 30 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | yesterday | MIT | A | 103 | Claude Code |