Skill Selector for Openclaw

Skill Selector is an orchestration utility that analyzes user intent and dynamically targets the most suitable installed capability using semantic and keyword matching.

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v1.3.0
Jun 18, 2026
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484
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Install & Download

1. ClawHub CLI

The fastest way to install a skill directly from the registry.

npx clawhub@latest install mimo-skill-selector

2. Manual Installation

Copy the skill folder to one of these locations

Global
~/.openclaw/skills/
Workspace
<project>/skills/

Priority: Workspace > Local > Bundled

3. Prompt Installation

Copy this prompt to OpenClaw to install it automatically.

Help me install mimo-skill-selector 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 Skill Selector?

Skill Selector serves as an automated traffic controller for environments utilizing Openclaw Skills. When workspaces scale and host numerous discrete operational modules, identifying the correct capability manually causes unnecessary friction. This skill evaluates runtime prompts to select the optimal capability, preventing analytical bottlenecks and maximizing overall pipeline throughput.

By leveraging dual-layered keyword and semantic evaluations, it reviews descriptions of available utilities and returns an ordered list of recommendations. This ensures that user instructions are consistently routed to the appropriate functional module without trial and error.

Skill Selector Use Cases

  • Managing an extensive library of specialized workspace utilities where manual routing introduces delays.
  • Standardizing semantic discovery layers across agent systems to automatically trigger relevant functions.
  • Clarifying broad or ambiguous execution requests before passing actionable payloads to target skills.
  • Constructing sequential multi-skill execution workflows where distinct task segments require different specialized modules.

How Skill Selector Works

  1. Intent Analysis: The skill intercepts incoming execution requests, parses structural keywords, and categorizes the underlying intent into specific domains such as content creation, data analysis, development tools, or digital marketing.
  2. Dynamic Cross-Matching: It scans descriptions of all installed options, executing parallel semantic and keyword matching routines to score relevance.
  3. Ranked Evaluation: Candidate modules are prioritized, presenting the top three options with clear, contextual justifications and defined operational scopes.
  4. Downstream Execution: Upon confirmation, the chosen module is initialized and populated with the original intent parameters to complete the loop.

Skill Selector Setup

To deploy this module within an orchestration environment, register the skill definition block inside your workspace config:

# Example CLI command to install and verify capabilities
openclaw install skill-selector
openclaw list --enabled

Ensure that all neighboring Openclaw Skills maintain populated description blocks to facilitate precise semantic alignment.

Skill Selector Data Schema & Taxonomy

The evaluation schema utilizes structured matching taxonomies to score installed configurations:

Attribute Type Operational Scope
intent_domain String Broad operational classification (e.g., development, analytics, marketing)
match_vector Float Multi-point semantic and literal compliance score
max_candidates Integer System limit restricting output to the top 3 high-probability configurations
fallback_status Boolean True when an absolute match is missing and closest partial alternatives are evaluated

Skill Selector Advanced Features

  • Anti-Rationalization Engine: Enforces strict programmatic boundaries preventing ambiguous response loops by forcing automated clarification limits (maximum of 2 iterations) and fallback options.
  • Pre-Filtering Triage: Optimizes evaluation latency by scoping target candidates down to localized task domains before running full vector matching cycles.
  • Downstream Context Transmission: Guarantees lossless handoffs by preserving raw, unfiltered intent properties when transitioning execution control to the target agent module.

SKILL.md


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