A powerful search orchestrator that breaks down complex tasks into parallel sub-tasks for specialized agents.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install searching-assistant
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install searching-assistant using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Searching Assistant?
The Searching Assistant acts as the strategic leader for search-related operations within the Openclaw Skills ecosystem. Its primary function is to serve as a leader of the searching group, analyzing high-level user queries and decomposing them into independent, complementary sub-tasks. This skill ensures that complex research is handled efficiently by distributing the workload among various specialized agents, such as the General Search Agent, while avoiding unsuitable resources like Academic Search when date-sensitive data is required. By acting as a central coordinator, it maximizes the breadth and depth of information retrieval for any given query.
Searching Assistant Use Cases
- Coordinating multi-faceted research projects that require data from diverse sources.
- Automating the decomposition of complex queries into parallel search streams using Openclaw Skills.
- Managing agent-based workflows where specific constraints like date-sensitivity must be respected.
- Enhancing search accuracy by delegating sub-tasks to the most relevant specialized agents.
How Searching Assistant Works
- The skill analyzes the user's input to determine the core objectives and constraints of the search task.
- It breaks the main task into a maximum of eight independent and complementary sub-tasks defined in natural language.
- The orchestrator identifies the most suitable agents for each sub-task within the Openclaw Skills framework, always including the General Search Agent.
- Sub-tasks are assigned in a single parallel operation to ensure maximum efficiency and reduced latency.
- The skill integrates runtime variables such as current date and session group ID to maintain context and accuracy during execution.
Searching Assistant Setup
To implement this search orchestration skill, include the searching-assistant configuration in your agent definitions. Ensure your environment supports runtime variable substitution for Openclaw Skills components.
# Install the searching assistant skill via your CLI
openclaw skills add searching-assistant
Ensure that template variables like $DATE$ are correctly mapped in your execution environment to allow the agent to handle date-specific requirements effectively.
Searching Assistant Data Schema & Taxonomy
The Searching Assistant manages data through a task-to-agent mapping system. It tracks the lifecycle of each search query through structured sub-task assignments.
| Metadata Field | Purpose |
|---|---|
| Task ID | Unique identifier for the search session within Openclaw Skills. |
| Sub-task List | Array of up to 8 natural language descriptions of specific search tasks. |
| Target Agent | The identifier for the agent responsible for a specific sub-task (e.g., General_Search_Agent). |
| Constraints | Logic flags used to include or exclude specific search agents based on query type. |
Searching Assistant Advanced Features
- Intelligent parallel task assignment to minimize information retrieval latency.
- Rule-based agent selection to optimize search relevance based on real-time query analysis.
- Native support for template variables like $DATE$ and $SESSION_GROUP_ID$ for context-aware search results.
- Seamless workflow management as a lead agent within the Openclaw Skills hierarchy, allowing for complex multi-agent search architectures.
SKILL.md
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