# Locate Steer And Improve A Practical Survey Of

> Mechanistic Interpretability (MI) has emerged as a vital approach to demystify the opaque decision-making of Large Language Models (LLMs). However, existing reviews primarily treat MI as an observational science, summarizing analytical insights while lacking a systematic framework for actionable intervention. To bridge this gap, we present a practical survey structured around the pipeline: 'Locate, Steer, and Improve.' We formally categorize Localizing (diagnosis) and Steering (intervention) met...

- Skill: `adu2021/locate-steer-and-improve-a-practical-survey-of` (Agent Skill)
- Install (CLI): `npx skillmds@latest add adu2021/locate-steer-and-improve-a-practical-survey-of`
- Raw SKILL.md: https://api.skillmd.com/api/skills/adu2021/locate-steer-and-improve-a-practical-survey-of/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: DevOps & Infra
- License: MIT
- Author: adu2021 (https://skillmd.com/u/adu2021)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/adu2021/locate-steer-and-improve-a-practical-survey-of

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## Overview

This skill covers research on locate, steer, and improve: a practical survey of actionable mechanistic interpretability. It addresses important challenges in agent development and evaluation.

## Key Insights

The paper provides:
- Novel approaches or frameworks for agent systems
- Empirical evaluation results and benchmarks
- Generalizable principles for practitioners

## When to Use

Use this skill when working on:
- Agent-based systems and applications
- Autonomous reasoning and planning
- Agent performance evaluation and improvement

## When NOT to Use

- For non-agent-related tasks
- When seeking implementation code (consult the paper)

## Resources

- ArXiv Abstract: https://arxiv.org/abs/2601.14004
- Full PDF: https://arxiv.org/pdf/2601.14004
- HTML: https://arxiv.org/html/2601.14004

Refer to the original paper for complete technical details, methodology, and experimental protocols.