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Install in OpenClaw
/install test-time-compute-guide
Description
Learn to enhance LLM performance using test-time compute with parallel sampling, sequential revision, and process reward models for better reasoning.
Usage Guidance
This is a documentation/guide skill with example code — not an executable package. Before implementing the examples, review any third-party PRM or model code you incorporate (the guide mentions a "custom process reward model") and avoid sending sensitive data to remote APIs or untrusted models. Expect higher compute and token costs when using best-of-N/parallel sampling and beam-search strategies. If you later install or copy third-party PRM implementations, vet their source, dependencies, and network behavior before running them.
Capability Analysis
Type: OpenClaw Skill
Name: test-time-compute-guide
Version: 1.0.0
The skill bundle is an educational guide focused on LLM reasoning techniques such as test-time compute and chain-of-thought. The code examples in SKILL.md are conceptual Python snippets for sampling and beam search that do not perform any risky operations, and the documentation contains no instructions designed to hijack the agent's behavior or exfiltrate data.
Capability Assessment
Purpose & Capability
Name/description (test-time compute, CoT, PRMs) align with the content. Declared dependencies (Transformers, custom PRM) are reasonable for implementing the described techniques. No unrelated environment variables, binaries, or config paths are requested.
Instruction Scope
SKILL.md contains explanatory text and small example snippets (Python pseudocode) showing how to implement parallel sampling, sequential revision, and beam search with a PRM. It does not instruct the agent to read arbitrary files, access unrelated environment variables, or transmit data to unexpected external endpoints.
Install Mechanism
No install spec is provided (instruction-only), so nothing will be downloaded or written to disk by the skill itself. This is the lowest-risk installation model.
Credentials
The skill does not request credentials or environment variables. The suggested dependencies (Transformers, custom PRM) are appropriate for the task. There are no suspiciously broad or unrelated secret requirements.
Persistence & Privilege
always is false and the skill is user-invocable only. It does not request permanent presence or make changes to other skills or system-wide settings.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install test-time-compute-guide - After installation, invoke the skill by name or use
/test-time-compute-guide - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
Initial release of test-time-compute-guide skill.
- Introduces core concepts of test-time compute (TTC) and chain-of-thought (CoT) reasoning for LLMs.
- Includes explanations of parallel sampling, sequential revision, process reward models, and self-consistency strategies.
- Provides practical guidance on when to use different reasoning approaches based on question difficulty.
- Features Python code examples demonstrating prompting, best-of-N sampling, and process-reward-guided beam search.
- Lists required dependencies for implementation.
Metadata
Frequently Asked Questions
What is Test Time Compute Guide?
Learn to enhance LLM performance using test-time compute with parallel sampling, sequential revision, and process reward models for better reasoning. It is an AI Agent Skill for Claude Code / OpenClaw, with 106 downloads so far.
How do I install Test Time Compute Guide?
Run "/install test-time-compute-guide" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is Test Time Compute Guide free?
Yes, Test Time Compute Guide is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does Test Time Compute Guide support?
Test Time Compute Guide is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created Test Time Compute Guide?
It is built and maintained by Robinyves (@robinyves); the current version is v1.0.0.
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