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Hebbrix

Hebbrix MCP Server

Official
by Hebbrix

hebbrix_mark_used

Adjust memory rankings by marking retrieved results as helpful or noisy, reinforcing useful memories and fading unused ones.

Instructions

Reinforce a memory you actually USED to answer (Hebbian recall): call this when a retrieved memory was helpful (helpful=True, strengthens it) or was noise (helpful=False, weakens it). Over time this makes the memories you rely on rank higher and unused ones fade. query is the question it helped answer, if handy.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryNo
helpfulNo
memory_idYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Addedv0.3.20

TDQS

A3.5/5.0
Behavior3/5

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

The description explains the Hebbian learning effect where memories are strengthened or weakened based on feedback—an appropriate side effect for the tool. However, it lacks explicit disclosure of whether the operation is a write-ahead log, partial update, or appends; it just says 'strengthens it' without detailing back-end behavior. No contradiction with annotations found.

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

Conciseness3/5

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

The description is a single, moderately long paragraph without line breaks or bolding to aid scanning. It front-loads the most important information but adds a somewhat conversational 'if handy' at the end, which slightly dilutes the formality. It's adequate but not elegantly structured.

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?

For a straightforward feedback tool with 3 parameters (1 required), the description covers the key dimensions: the `helpful` side effect, the `query` purpose, and the meta-insight about memory ranking. Since an output schema exists, the lack of return-value documentation is not a gap.

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

Parameters4/5

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

With 0% schema coverage, the description carries the full burden, and it delivers well. It clarifies the `helpful` boolean as a strengthen/weaken switch and describes `query` as 'the question it helped answer.' However, it only implicitly covers memory_id by referring to 'a memory' without explicitly naming the parameter.

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 clear action verbs like 'Reinforce a memory you actually USED' and explains the mechanism of strengthening/weakening, distinguishing it from sibling tools like hebbrix_remember or hebbrix_log_decision. It could be more explicit by using the tool's name 'mark_used' directly, but it's unambiguous about the core action.

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

Usage Guidelines3/5

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

The description provides explicit when-to-use guidance: 'call this when a retrieved memory was helpful... or was noise.' However, it fails to mention exclusions or alternatives like 'use hebbrix_get for retrieval instead.' The guidance is implied from sibling names but never confirmed.

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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