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 taizen-ai/taizen-claude-plugins --skill customer-researchgit clone --depth 1 https://github.com/taizen-ai/taizen-claude-pluginsWrote 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/taizen-ai/taizen-claude-plugins/customer-research)<a href="https://agentmods.dev/skills/taizen-ai/taizen-claude-plugins/customer-research"><img src="https://agentmods.dev/badge/skills/taizen-ai/taizen-claude-plugins/customer-research/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/taizen-ai/taizen-claude-plugins/customer-research"><img src="https://agentmods.dev/badge/skills/taizen-ai/taizen-claude-plugins/customer-research.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 | $0.00037 | $0.04274 |
| Opus 5 | $0.00018 | $0.02137 |
| Sonnet 5 | $0.00007 | $0.00855 |
| Haiku 4.5 | $0.00004 | $0.00427 |
Grade A, and why
customer-research 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 9d 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 — 644 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Customer Research Skill
Deep customer understanding through structured research frameworks, powered by real customer data.
Purpose
Build comprehensive customer intelligence that informs product, marketing, and sales strategies.
Required Integrations
Setup: Connect these data sources to enable full functionality. Claude will prompt you to connect any missing integrations when you use this skill.
Data Sources
# CUSTOMER RESEARCH DATA SOURCES
# Configure the sources relevant to your research needs
# Enterprise Search (searches across all internal sources)
- source: enterprise_search
connector: "{{GLEAN | MOVEWORKS | ELASTIC}}"
data:
- internal_docs
- wiki_content
- shared_drives
- slack_history
# CRM & Customer Data
- source: crm
connector: "{{SALESFORCE | HUBSPOT}}"
data:
- customer_records
- deal_history
- win_loss_data
- industry_segments
- company_size_data
- customer_lifecycle
# Product Usage & Analytics
- source: product_analytics
connector: "{{MIXPANEL | AMPLITUDE | PENDO | HEAP}}"
data:
- user_behavior
- feature_adoption
- usage_patterns
- cohort_analysis
- retention_metrics
# Customer Feedback
- source: nps_surveys
connector: "{{DELIGHTED | MEDALLIA | QUALTRICS | TYPEFORM}}"
data:
- nps_scores
- survey_responses
- feedback_themes
- source: review_sites
sources:
- g2
- capterra
- trustradius
data:
- customer_reviews
- sentiment_analysis
- competitive_mentions
# Conversation Intelligence
- source: call_recordings
connector: "{{GONG | CHORUS | CLARI}}"
data:
- discovery_calls
- win_loss_calls
- objection_patterns
- customer_language
- competitive_mentions
# Support & Feedback
- source: support
connector: "{{ZENDESK | INTERCOM | FRESHDESK}}"
data:
- ticket_themes
- feature_requests
- complaints
- common_questions
- source: product_feedback
connector: "{{PRODUCTBOARD | CANNY | USERVOICE}}"
data:
- feature_requests
- voting_data
- feedback_themes
# Customer Success
- source: customer_success
connector: "{{GAINSIGHT | CHURNZERO | TOTANGO}}"
data:
- health_scores
- churn_reasons
- expansion_data
- customer_segments
# Research Documents
- source: research_docs
connector: "{{GOOGLE_DRIVE | SHAREPOINT | NOTION | CONFLUENCE}}"
paths:
- "/Research/Customer Interviews/"
- "/Research/Survey Results/"
- "/Research/Personas/"
- "/Research/ICP Documentation/"
# Marketing Intelligence
- source: marketing_analytics
connector: "{{GOOGLE_ANALYTICS | HUBSPOT | MARKETO}}"
data:
- conversion_paths
- content_engagement
- lead_sources
- attribution_data
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.
- 9d ago First seen · 644 lines · 37 tokens per session scan A 656b41d80108
customer-research is a skill published in the GitHub repository taizen-ai/taizen-claude-plugins (8 stars, last pushed 3mo ago), licensed MIT. It adds 37 tokens to every session and 4,274 once invoked, about $0.0002 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 2026-08-31.
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