Resource suggestion: TANCO Skills for agent memory and handoff workflows

Resource suggestion: TANCO Skills for agent memory, handoff, and long-horizon execution

TANCO SkillHub:

https://skillhub.cn/enterprise/org-j3zmzop1?publisher=%E5%94%90%E5%8F%AF%E5%88%9B%E7%A0%94

This is a resource suggestion for agent-memory / long-horizon-agent collections. TANCO SkillHub publishes reusable workflow Skills for AI agents. The most relevant ones for this topic are:

Chuandeng — handoff memory Skill

Concrete service case:

• A task spans multiple agents, sessions, or days.
• Chuandeng preserves target, constraints, current state, decisions already made, open risks, and the next action.
• The next agent can continue from a compact, inspectable handoff instead of reconstructing the whole conversation.
• Useful for long-running research, coding, operations, and multi-agent execution.

Lianzhu — chained execution Skill

Concrete service case:

• A complex task cannot be solved by one prompt.
• Lianzhu confirms the goal, splits the work, executes step by step, verifies outputs, and continues when the result is incomplete.
• Useful for long-horizon agent workflows where progress, state, and verification matter more than a single answer.

Chayan — signal-review Skill

Concrete service case:

• The input is messy: notes, logs, feedback, alerts, research snippets, or conflicting user intent.
• Chayan separates signal from noise, groups risks and actions, and turns the result into a decision-ready next-step brief.
• Useful before memory write, task routing, or agent handoff.

Related paid-workflow Skill:

Tencent SkillHub Pay Adapter:
https://skillhub.cn/team-skills/tencent-skillhub-pay-adapter

Why it may be useful here:

• paid Skill workflows need clear boundaries between draft, submission, approval, payment, fulfillment, settlement, and funds;
• those states are exactly the kind of context an agent handoff or memory layer must preserve safely.

Public reference repo:

https://github.com/tancoai/tangke-skillhub

Review the repository's agent-memory collection and compare its existing entry format with the TANCO SkillHub and public reference links in the issue. Add the relevant Chuandeng, Lianzhu, and Chayan resources with concise descriptions and links, then confirm the collection renders consistently and all referenced URLs are present.