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Hebbrix

Hebbrix MCP Server

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by Hebbrix

hebbrix_confidence

Evaluate agent confidence using stored memory and past decision outcomes to determine if autonomous action is advisable. Returns a confidence score and a recommended action.

Instructions

Ask how confident the agent should be before acting on something, grounded in stored memory and past decision outcomes. Call this before a consequential autonomous action. Returns a confidence score and a recommended action.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
collection_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries full burden. It discloses that the tool returns a confidence score and recommended action based on memory, but it does not explicitly state whether it is read-only or has side effects. The behavioral info is adequate but not exhaustive.

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

Conciseness5/5

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

The description is three sentences, concise and front-loaded. Each sentence adds value: purpose, usage timing, and output. No superfluous 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?

Despite having an output schema, the description is incomplete because it fails to explain parameter semantics (2 params, one optional). The description does not cover what 'collection_id' is for or how the query influences the confidence, leaving significant gaps for a tool that likely requires specific input context.

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

Parameters1/5

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

Schema description coverage is 0%, so the description must explain parameter meanings. It only implies a 'query' but does not describe 'query' or 'collection_id' in any detail, leaving the agent without guidance on what inputs are expected or how they affect results.

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

Purpose5/5

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

The description clearly states the tool's purpose: to assess confidence based on stored memory and past outcomes, returning a score and recommended action. It distinguishes itself from siblings by focusing on confidence, a unique function among the listed tools.

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

Usage Guidelines4/5

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

The description explicitly advises to call this 'before a consequential autonomous action,' providing clear context. However, it does not mention when not to use it or specify alternatives, though sibling tools imply different use cases.

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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