ClawKit Logo
ClawKitReliability Toolkit
Back to Registry
Official Verified

utility

Score candidate agent actions by expected gain, cost, uncertainty, and redundancy to guide dispatch and termination decisions

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/athola/nm-leyline-utility
Or

Night Market Skill — ported from claude-night-market/leyline. For the full experience with agents, hooks, and commands, install the Claude Code plugin.

Utility Skill

Overview

A decision framework for agent orchestration based on Liu et al., "Utility-Guided Agent Orchestration for Efficient LLM Tool Use" (arXiv:2603.19896). Each candidate action is scored by subtracting weighted costs from expected gain, producing a single utility value that guides action selection. The framework prevents over-calling tools and premature stopping by making both errors costly. Utility range is [-2.3, 1.0].

When To Use

  • Deciding whether to dispatch another agent or tool call
  • Gating expensive tool calls (search, code execution, delegation)
  • Selecting the right model tier for a sub-task
  • Continuation decisions after receiving partial results
  • Verification gating before writing or committing output

When NOT to Use

  • Single-step operations with one obvious action
  • Trivial tasks where cost of scoring exceeds benefit
  • Already-committed actions that cannot be undone

Action Space

A = {respond, retrieve, tool_call, verify, delegate, stop}

ActionDescription
respondEmit a final answer from current context
retrieveFetch additional information (search, read, lookup)
tool_callExecute a tool (code runner, API, file write)
verifyCheck a prior result for correctness or completeness
delegateSpawn a sub-agent or hand off to a specialist
stopTerminate the loop and return current state

Utility Function

U(a | s_t) = Gain(a | s_t)
           - λ₁ · StepCost(a | s_t)
           - λ₂ · Uncertainty(a | s_t)
           - λ₃ · Redundancy(a | s_t)
ParameterDefaultRationale
λ₁1.0Cost baseline; all other weights relative to this
λ₂0.5Weak empirical correlation with outcome (r=0.0131)
λ₃0.8Redundancy pruning yields ~10% token savings

Utility range: [-2.3, 1.0]. Positive values indicate the action is worth taking. Values below the floor (-0.5 default) indicate the action should be skipped.

Termination Conditions

Stop the loop when any of the following is true:

  • (a) Selected action is stop
  • (b) Step budget exhausted (default: 10 steps)
  • (c) All non-stop actions score below the floor (default: -0.5)

High-gain override: If Gain >= 0.7 for any action, condition (c) may be overridden. Document the override and the gain value in your reasoning trace.

Quick Start

Minimal 4-step advisory pattern:

Metadata

Author@athola
Stars4473
Views0
Updated2026-05-01
View Author Profile
AI Skill Finder

Not sure this is the right skill?

Describe what you want to build — we'll match you to the best skill from 16,000+ options.

Find the right skill
Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-athola-nm-leyline-utility": {
      "enabled": true,
      "auto_update": true
    }
  }
}
Safety NoteClawKit audits metadata but not runtime behavior. Use with caution.