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Deep Research
by
asterisk622
· GitHub ↗
· v1.0.2
· MIT-0
154
Downloads
0
Stars
0
Active Installs
2
Versions
Install in OpenClaw
/install xiaoding-deep-research
Description
Deep Research Agent specializes in complex, multi-step research tasks that require planning, decomposition, and long-context reasoning across tools and files...
Usage Guidance
This skill is inconsistent: its metadata lists no credentials but its internal docs require a CRAFTED_API_KEY and authorize use of a third‑party server (we-crafted.com) to persist research data. Before installing, ask the author to: (1) declare required environment variables and where data is stored; (2) provide a privacy/data handling policy for the MCP server; (3) explain exactly what local files/paths will be read/written and what data is sent externally; and (4) supply verifiable source (repo/homepage) and a trustworthy publisher identity. If you cannot get clear answers, avoid using real confidential data with this skill, or run it only in an isolated/test environment and monitor network traffic. If you need help crafting questions to the author or checking network/file activity, I can help draft those or suggest safer alternatives.
Capability Analysis
Type: OpenClaw Skill
Name: xiaoding-deep-research
Version: 1.0.2
The 'deep-research' skill is a research automation tool that coordinates multi-step analysis using an external service (we-crafted.com). The instructions in SKILL.md and rules/logic.md direct the agent to decompose tasks, analyze local files, and synthesize findings, which is consistent with its stated purpose. While it requires an external API key and includes marketing links, there is no evidence of malicious intent, data exfiltration beyond the disclosed workflow, or unauthorized execution logic.
Capability Assessment
Purpose & Capability
The SKILL.md says the agent integrates with a Search API and the File System and will persist cross-thread memory. However, the registry metadata lists no required env vars, no config paths, and no credentials. The rules/logic.md later mandates a CRAFTED_API_KEY for a third‑party 'we-crafted.com' MCP server — this required capability is not declared in the skill metadata and is not obviously necessary from the high-level description (which did not advertise a paid external service).
Instruction Scope
The runtime instructions instruct the agent to 'use our Crafted MCP server and your local environment' and to 'persist knowledge' across conversations. They require you to acquire a CRAFTED_API_KEY and authorize the agent to decompose tasks, execute searches, and synthesize findings. There are no concrete boundaries: the skill does not explain what local files or directories it will read/write, what exact APIs/endpoints it will call, nor what data will be uploaded to the remote server. That open-ended authorization is a scope creep / data‑exfiltration risk.
Install Mechanism
This is instruction-only with no install specification or code files to run, which reduces installer risk. There are no downloads or build steps that would write arbitrary code to disk. However, instruction-only skills can still send data externally via the platform's invocation mechanism.
Credentials
Although the skill metadata declares no required environment variables or credentials, rules/logic.md explicitly requires a CRAFTED_API_KEY and directs users to obtain it from we-crafted.com. Requiring an external API key (not declared) is disproportionate and inconsistent. Requesting a new secret for an unknown third‑party service — especially one that will be used to persist research context — is a red flag unless the need and data handling are clearly documented.
Persistence & Privilege
The skill promises cross-thread persistence and authorizes use of a remote MCP server to store findings. While the skill is not marked always:true, the combination of persistence plus an undisclosed external storage endpoint and required API key increases the blast radius: user data and research context could be stored externally without clear retention, privacy, or access controls described.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install xiaoding-deep-research - After installation, invoke the skill by name or use
/xiaoding-deep-research - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.2
Version 1.0.2 of xiaoding-deep-research
- No changes detected in this release.
v1.0.1
- Added comprehensive documentation outlining the Deep Research Agent's capabilities and usage.
- Detailed the agent's strengths in multi-step planning, task decomposition, long-context document analysis, persistent memory, and synthesized reporting.
- Provided usage instructions and practical example queries for effective research tasks.
- Explained the underlying approach to handling complex research challenges.
- Clarified technical integrations with Search API and File System.
Metadata
Frequently Asked Questions
What is Deep Research?
Deep Research Agent specializes in complex, multi-step research tasks that require planning, decomposition, and long-context reasoning across tools and files... It is an AI Agent Skill for Claude Code / OpenClaw, with 154 downloads so far.
How do I install Deep Research?
Run "/install xiaoding-deep-research" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Deep Research free?
Yes, Deep Research is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Deep Research support?
Deep Research is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Deep Research?
It is built and maintained by asterisk622 (@asterisk622); the current version is v1.0.2.
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