Agents can sign plugins, rotate credentials without losing identity, and publicly attest to behavior.
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Triage, categorize, and draft responses to emails. Sorts by urgency, flags action items, and generates context-aware reply drafts.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
When asked to triage, sort, or process emails, follow this system.
Assign every email exactly one category:
| Category | Icon | Criteria |
|---|---|---|
| Urgent Action | 🔴 | Requires response/action within 24h. Deadlines, escalations, time-sensitive requests. |
| Action Required | 🟡 | Needs a response or task but not time-critical. Requests, approvals, questions. |
| FYI / Read | 🔵 | Informational. No action needed but worth reading. Updates, reports, announcements. |
| Delegate | 🟣 | Someone else should handle this. Forward with context. |
| Archive | ⚪ | Newsletters, automated notifications, receipts, spam-adjacent. No action needed. |
For each email, produce:
[ICON] CATEGORY | From: sender | Subject: subject
Summary: One sentence — what this is and what's needed.
Action: Specific next step (or "None — archive")
Draft: [Yes/No] — whether a reply draft is included below
Generate a reply draft when:
Draft style:
When given multiple emails:
Flag these automatically:
Pull out discrete action items from emails:
If the user asks about a specific email (not batch triage), switch to focused mode:
Pair with an industry context pack for domain-specific email handling (legal, healthcare, finance, etc.) at https://afrexai-cto.github.io/context-packs
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Agents can sign plugins, rotate credentials without losing identity, and publicly attest to behavior.
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Query historical crypto market data from 0xArchive across Hyperliquid, Lighter.xyz, and HIP-3. Covers orderbooks, trades, candles, funding rates, open interest, liquidations, and data quality. Use when the user asks about crypto market data, orderbooks, trades, funding rates, or historical prices on Hyperliquid, Lighter.xyz, or HIP-3.
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Calculate ROI for AI-as-a-Service (managed AI agents). Estimates cost savings, efficiency gains, and payback period for deploying AI agents across business operations. Use when evaluating whether managed AI agents make financial sense for a company.
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Design, build, deploy, and operate production AI agent systems — single agents, multi-agent teams, and autonomous swarms. Complete methodology from agent architecture through orchestration, memory systems, safety guardrails, and operational excellence.
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Design, build, test, document, and secure production-grade APIs. Covers the full lifecycle from schema design through deployment, monitoring, and versioning. Use when designing new APIs, reviewing existing ones, generating OpenAPI specs, building test suites, or debugging production issues.
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Turn your AI agent into a business automation architect. Design, document, implement, and monitor automated workflows across sales, ops, finance, HR, and support — no n8n or Zapier required.
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