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manncodes

Neuronpedia MCP Server

by manncodes

steer_generation

Control AI model outputs by adjusting the activation of a specific feature during text generation, enabling targeted influence over generated content.

Instructions

Steer model generation using a specific feature

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
layerYesLayer number
modelYesModel name
isChatNoWhether this is a chat model (default: false)
promptYesGeneration prompt
featureYesFeature number
steeringStrengthYesSteering strength (-10 to 10)
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries full burden. It discloses the action ('steer model generation') but fails to mention behavioral traits such as whether the tool is destructive, requires authentication, affects model state, or produces side effects. The term 'steer' is vague without further elaboration.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single sentence that is front-loaded with the verb and resource. It is concise, but could be slightly improved by expanding on the effect of steering. Nonetheless, no filler words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool has 6 parameters, no output schema, and no annotations, the description is insufficient. It does not explain what the tool returns, the behavior of steering, or any constraints. The description is too minimal for the tool's complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, with each parameter having a description. The tool description adds no additional meaning beyond what the schema already provides, so a baseline of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a clear verb ('steer') and identifies the resource ('model generation') and scope ('using a specific feature'). It distinguishes itself from sibling tools like 'generate_explanation' or 'search_explanations' by implying a modification during generation, though it doesn't explicitly contrast with them.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives (e.g., when to choose 'steer_generation' over 'generate_explanation'). No mention of prerequisites, exclusions, or recommended contexts.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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