Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Drive Smithers durable workflows from OpenClaw. Use for multi-step, long-running, background, human-in-the-loop, retryable, or repeatable work. Prefer creating or improving a Smithers workflow over repeating ad-hoc agent turns, and use evals plus optimization to improve workflows over time.
Compare two structured agent-run artifacts to estimate cache efficiency, explain likely cache breaks, and produce a local benchmark report. Use when a user wants to understand whether a prompt layout, tool manifest, or history shape is helping or hurting prompt-cache reuse.
Plan and inspect prompt-cache behavior for long-running Claude agent loops. Use when a user wants to split stable tool, system, and history context into cacheable layers, compare captured cache metadata, estimate cost impact from supplied pricing inputs, or keep durable memory outside the cached prefix.
Provides weighted scoring, rubrics, and decision-threshold patterns. Use when designing quality gates, evaluation systems, or decision frameworks.
Audit Skill() refs; detect hubs, isolates, and dangling targets. Use when auditing skills.
Coordinates Claude agent teams via filesystem protocol. Use when orchestrating parallel agents with task dependencies. Do not use for single-agent tasks.
Autonomous decision loop with reflection and iteration
Explain plugin, skill, command, agent, and hook mechanics used here. Use when authoring or debugging plugins. Do not use for ops; use night-market-operations.
Manages context overflow by handing off to a fresh subagent at 80% usage. Use when context pressure is critical and work must continue uninterrupted.
Recommends context compression strategies for bloated or quota-heavy sessions. Use when context feels sluggish or quota burns faster than expected.