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Hebbrix

Hebbrix MCP Server

Official
by Hebbrix

hebbrix_confidence

Read-onlyIdempotent

Assess confidence before autonomous actions using stored memories and past outcomes. Detect numeric rule violations and return a confidence score with a recommended action to proceed or halt.

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.

If the action VIOLATES a stored numeric rule (e.g. opening a 600-line PR when a memory says "PRs must be < 400 lines"), the result includes a constraint_conflict block and recommended_action is do_not_act.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
collection_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.3.3

TDQS

A4.3/5.0
Behavior5/5

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

Annotations already indicate readOnly, idempotent, non-destructive behavior. The description adds valuable context: it returns a confidence score and recommended action, and it handles constraint violations with a dedicated block and do_not_act recommendation. This goes beyond annotation-provided safety info, with no contradictions.

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 concise and well-structured: first paragraph covers purpose and usage, second paragraph details a special edge case. No redundant sentences; every sentence earns its place.

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

Completeness4/5

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

Given the tool's moderate complexity and the presence of an output schema, the description covers purpose, when to use, return value, and conflict behavior. The main gap is parameter semantics, but overall it is sufficiently complete for an agent to select the tool confidently. Slightly docked for not explaining query/collection_id.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate. However, it never explains what the 'query' parameter should contain (e.g., the proposed action or situation) or the purpose of 'collection_id'. The high-level phrasing implies query is the action, but this is not explicit, leaving agents guessing at invocation details.

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 function: asking how confident the agent should be before acting, grounded in stored memory and past outcomes. It distinguishes itself from siblings by specifying the return of a confidence score and recommended action, and the constraint_conflict block for numeric rule violations.

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 provides an explicit when-to-use directive: 'Call this before a consequential autonomous action.' It does not explicitly name alternatives or exclusion cases, but the context makes the intended usage clear. A minor gap versus naming a specific alternative tool.

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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