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Hebbrix

Hebbrix MCP Server

Official
by Hebbrix

hebbrix_create_procedure

Create a tenant-scoped learned procedure with condition and action inputs to give AI agents reusable procedural memory for cross-session reasoning.

Instructions

Create a tenant-scoped learned procedure using canonical API fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
actionYes
run_idNo
user_idNo
agent_idNo
categoryNo
conditionYes
parametersNo
descriptionNo
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. Addedv0.5.8

TDQS

B3/5.0
Behavior3/5

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

The description correctly indicates a write operation, consistent with readOnlyHint=false, and adds that the object is tenant-scoped. However, it does not explain creation semantics such as duplicate behavior, required tenant context, or how 'learned' affects persistence, so it adds only modest context beyond the annotations.

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?

The description is a single front-loaded sentence with no redundant words. It loses one point because the phrase 'canonical API fields' is vague and could mislead, but it is otherwise economically structured.

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?

The description identifies the resource type and tenant scope, and output schema provides return-shape context, but it is far too thin for a 10-parameter create tool with two free-form nested objects. The agent is left without guidance on required field semantics, relationships between run_id/user_id/agent_id, or how condition and action are structured.

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?

With 10 parameters and 0% schema description coverage, the description needed to explain the open-ended condition/action objects and the optional identifiers, but it only says 'canonical API fields' without identifying any of them. An agent cannot determine what to place in name, condition, action, parameters, or collection_id.

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 names a clear action ('Create'), a specific resource ('tenant-scoped learned procedure'), and the required input style ('canonical API fields'). It is readily distinguished from siblings like hebbrix_update_procedure, hebbrix_delete_procedure, and hebbrix_get_procedure.

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 when-to-use guidance is provided: it does not say when to choose this over hebbrix_update_procedure, hebbrix_remember, or hebbrix_execute_procedure, and it gives no prerequisites or constraints. The intended usage must be inferred solely from the sibling names.

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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