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.
git clone --depth 1 https://github.com/abinauv/business-consultingWrote 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/commands/abinauv/business-consulting/customer-analysis)<a href="https://agentmods.dev/commands/abinauv/business-consulting/customer-analysis"><img src="https://agentmods.dev/badge/commands/abinauv/business-consulting/customer-analysis.svg" alt="Measured on agentmods" 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 | $0.00012 | $0.00455 |
| Opus 5 | $0.00006 | $0.00228 |
| Sonnet 5 | $0.00002 | $0.00091 |
| Haiku 4.5 | $0.00001 | $0.00046 |
Grade A, and why
customer-analysis 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 7d 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 — 36 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customer Analysis
Use the business-consulting:customer-insights skill to deliver a comprehensive customer analysis.
Analysis Steps
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Customer Segmentation — Segment customers by value, behavior, needs, or demographics. Identify the highest-value segments and underserved segments. Present a segmentation table with size, revenue contribution, growth rate, and strategic priority.
-
Customer Journey Map — Map the end-to-end journey (awareness → consideration → purchase → onboarding → usage → renewal → advocacy). For each stage, document:
Stage Customer Actions Touchpoints Emotions Pain Points Opportunities -
Persona Development — Create 2–3 data-driven personas for key segments. Each persona should include: demographics, goals, frustrations, behaviors, decision criteria, preferred channels, and representative quotes.
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Satisfaction & NPS Driver Analysis — Identify the key drivers of customer satisfaction and detraction. Use a driver importance vs. performance matrix to prioritize improvement areas.
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Churn Analysis — Analyze churn patterns by segment, tenure, and cohort. Identify leading indicators of churn risk. Calculate the cost of churn and ROI of retention interventions.
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Customer Lifetime Value — Calculate CLV by segment. Identify levers to increase CLV (reduce churn, increase ARPU, improve onboarding, cross-sell/up-sell).
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Win/Loss Patterns — Identify why customers choose you (win themes) and why they don't (loss themes). Present patterns with frequency and strategic implications.
-
Recommendations — Prioritize customer experience improvements by impact and feasibility. Include quick wins (0–30 days) and strategic initiatives (3–12 months).
Output Requirements
- Lead with the most actionable insight ("The biggest opportunity is...")
- Use tables for journey maps, segmentation, and driver analysis
- Quantify everything: segment sizes, CLV, churn rates, cost of churn, ROI of improvements
- Include a prioritized action plan with owners and timelines
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.
- 7d ago First seen · 36 lines · 12 tokens per session scan A 52fa4f660e04
customer-analysis is a command published in the GitHub repository abinauv/business-consulting (27 stars, last pushed 6mo ago), licensed MIT. It adds 12 tokens to every session and 455 once invoked, about $0.0001 per session on Opus 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 2026-08-30.
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