← Back to Skills Marketplace
63
Downloads
0
Stars
0
Active Installs
1
Versions
Install in OpenClaw
/install real-estate-deep-research
Description
深度智联 Agentic 智能体 Skill。让用户告别碎片化查询，由 AI 智能体统筹复杂的房地产行业研究任务。支持房地产市场分析、土地研判、房地产企业分析、房地产项目案例分析、房地产项目设计建议、政策解读、物业行业资讯（日/周/月报）、物业行业招投标监测等房地产行业研究任务的创建、进度查询、成果获取与迭代优化...
Usage Guidance
This skill appears to do what it says: it is a Python CLI that forwards tasks and uploaded files to agentic.dichanai.com and requires a single AGENTIC_TOKEN. Before installing, consider: 1) Trust the remote service (agentic.dichanai.com) — any files you upload or prompts you send will be transmitted to that host. 2) The CLI auto-renews tokens and prints NEW_TOKEN to stdout; ensure your agent or user-facing outputs will not disclose that printed token (use ephemeral tokens, restrict logs, or avoid running token-renew on a public channel). 3) Confirm what 'uv' install means in your platform and whether the package installation is performed from a trusted source. 4) Avoid uploading highly sensitive files (PII, private keys) unless you fully trust the endpoint and its data retention policies. 5) Note small inconsistencies (version string mismatch in SKILL.md vs metadata, script contains a name typo) — these suggest limited quality control; review the script source yourself or ask the publisher for clarifications. If you need lower risk, request a version that does not print tokens to stdout and that documents the installer provenance (pip/requirements).
Capability Assessment
Purpose & Capability
Name/description, required binary (python3), required env var (AGENTIC_TOKEN), and the CLI code all align: the skill implements a client for agentic.dichanai.com to create/monitor/download research tasks. Requiring a token and python is proportionate to the described functionality.
Instruction Scope
SKILL.md explicitly instructs the agent to send user instructions and any uploaded reference files to agentic.dichanai.com — this is coherent with the service but is a privacy surface the user must accept. The SKILL.md asks the AI to check token state and to avoid leaking tokens, however the implementation prints renewed tokens to stdout which could be captured and leaked by the agent or logged — this is a concrete instruction-scope risk (sensitive data exposure).
Install Mechanism
Declared install is a single package 'requests' (reasonable for a Python CLI). The metadata uses 'kind: uv' which is nonstandard/odd (not a well-known installer label like pip/brew); this is a minor inconsistency to verify with the platform but not inherently malicious.
Credentials
Only AGENTIC_TOKEN is requested as the primary credential which matches the skill's remote API usage. The concern is proportionality of how the token is handled: the CLI will automatically renew tokens and prints NEW_TOKEN to stdout for the operator to copy — this increases the chance a token is exposed to users, logs, or the agent's outgoing messages.
Persistence & Privilege
always is false and there is no evidence the skill requests permanent platform-wide privileges or modifies other skills' configurations. Autonomous invocation remains enabled (platform default) but is not combined with other high-privilege indicators.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install real-estate-deep-research - After installation, invoke the skill by name or use
/real-estate-deep-research - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
real-estate-deep-research 1.1.0 introduces a comprehensive agent-based workflow for deep real estate research.
- Adds a guided conversation system to help users clarify and improve research requests prior to task submission.
- Implements strict adherence to user intent: user prompts are passed verbatim to backend without AI reinterpretation or rewriting.
- Integrates with 深度智联 Agentic 智能体 for unified handling of complex research tasks (market/land analysis, project studies, policy interpretation, reporting, etc.).
- Enforces proactive user notification regarding token usage, privacy, and consumption of platform credits before task execution.
- Detailed HITL (“human-in-the-loop”) protocol: system pauses and relays AI agent questions precisely when user input or decisions are needed.
- Expands command set for full lifecycle management, including scheduling, uploading, downloading, aborting, and sharing research projects.
Metadata
Frequently Asked Questions
What is DeepLink Agentic?
深度智联 Agentic 智能体 Skill。让用户告别碎片化查询，由 AI 智能体统筹复杂的房地产行业研究任务。支持房地产市场分析、土地研判、房地产企业分析、房地产项目案例分析、房地产项目设计建议、政策解读、物业行业资讯（日/周/月报）、物业行业招投标监测等房地产行业研究任务的创建、进度查询、成果获取与迭代优化... It is an AI Agent Skill for Claude Code / OpenClaw, with 63 downloads so far.
How do I install DeepLink Agentic?
Run "/install real-estate-deep-research" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is DeepLink Agentic free?
Yes, DeepLink Agentic is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does DeepLink Agentic support?
DeepLink Agentic is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created DeepLink Agentic?
It is built and maintained by 深度智联 (@dichanai); the current version is v1.0.0.
More Skills