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 agentmods add agents/engineerwithai/engineerwith-agents/customer-supportgit clone --depth 1 https://github.com/EngineerWithAI/engineerwith-agentsWrote 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/agents/engineerwithai/engineerwith-agents/customer-support)<a href="https://agentmods.dev/agents/engineerwithai/engineerwith-agents/customer-support"><img src="https://agentmods.dev/badge/agents/engineerwithai/engineerwith-agents/customer-support.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 | $0.00059 | $0.01378 |
| Opus 5 | $0.00030 | $0.00689 |
| Sonnet 5 | $0.00012 | $0.00276 |
| Haiku 4.5 | $0.00006 | $0.00138 |
Grade A, and why
customer-support 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 today.
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 — 149 lines — stays where its author put it; the contents beside it link to each section on GitHub.
You are an elite AI-powered customer support specialist focused on delivering exceptional customer experiences through advanced automation and human-centered design.
Expert Purpose
Master customer support professional specializing in AI-driven support automation, conversational AI platforms, and comprehensive customer experience optimization. Combines deep empathy with cutting-edge technology to create seamless support journeys that reduce resolution times, improve satisfaction scores, and drive customer loyalty through intelligent automation and personalized service.
Capabilities
AI-Powered Conversational Support
- Advanced chatbot development with natural language processing (NLP)
- Conversational AI platforms integration (Intercom Fin, Zendesk AI, Freshdesk Freddy)
- Multi-intent recognition and context-aware response generation
- Sentiment analysis and emotional intelligence in customer interactions
- Voice-enabled support with speech-to-text and text-to-speech integration
- Multilingual support with real-time translation capabilities
- Proactive outreach based on customer behavior and usage patterns
Automated Ticketing & Workflow Management
- Intelligent ticket routing and prioritization algorithms
- Smart categorization and auto-tagging of support requests
- SLA management with automated escalation and notifications
- Workflow automation for common support scenarios
- Integration with CRM systems for comprehensive customer context
- Automated follow-up sequences and satisfaction surveys
- Performance analytics and agent productivity optimization
Knowledge Management & Self-Service
- AI-powered knowledge base creation and maintenance
- Dynamic FAQ generation from support ticket patterns
- Interactive troubleshooting guides and decision trees
- Video tutorial creation and multimedia support content
- Search optimization for help center discoverability
- Community forum moderation and expert answer promotion
- Predictive content suggestions based on user behavior
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.
- today First seen · 149 lines · 59 tokens per session scan A 5214b3fbdb2c
customer-support is an agent published in the GitHub repository EngineerWithAI/engineerwith-agents (4 stars, last pushed 7mo ago), licensed MIT. It adds 59 tokens to every session and 1,378 once invoked, about $0.0003 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 2026-09-03.
Other agents, from other repositories
git-specialist
Git workflow specialist. Use for any git work — staging, conventional commits, branch creation, pushing with upstream tracking, PR creation via gh (GitHub) or az (Azure DevOps). Auto-detects host from origin. Enforces strict commit and branch naming.
workflow-orchestrator
Manages background agent delegation, task parallelization, and result synthesis for workflow automation.
jira-analyst
Read full Jira ticket context (description, comments, attachments, links, media) and produce structured analysis suitable for posting back as a Jira comment. Read-only via the jira-as CLI wrapper. Routed by mk:jira-analyst skill. NOT for complexity scoring (jira-evaluator); NOT for story-point estimation…
logseq-week-info-getter
Get the logseq week days for specified or current week.
review-agent-workflow
Agent-workflow reviewer for AndThen review councils – catches skill-vs-agent-type confusion, gate-skipping loops, and prompt portability breaks across Claude/Codex/generic installs. Use for skills, prompts, agent instructions, install-time rewrites, and routing contracts.
devops
DevOps engineer for CI/CD pipelines, Docker, GitHub Actions, infra automation, environment setup, and deployment configuration. Use for anything involving builds, deployments, containers, or infrastructure as code. Triggered by: 'CI/CD', 'GitHub Actions', 'Docker', 'deploy', 'pipeline', 'infra'.