Skip to main content
Glama
Hebbrix

Hebbrix MCP Server

Official
by Hebbrix

hebbrix_log_decision

Log an agent decision and its outcome to build long-term memory, improving future recommendations. After a confidence check, record just the outcome to close the loop.

Instructions

Record a decision the agent made and, if known, its outcome (success | failure | partial). This feeds hebbrix_confidence so future recommendations improve. Log both the choice and how it turned out.

Shortcut: right after a hebbrix_confidence check you can log just the outcome (e.g. outcome="success") with no description — it auto-fills from the thing you just asked about, closing the confidence -> action -> outcome loop with one call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
outcomeNo
descriptionNo
collection_idNo
decision_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

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

  1. Changed4 schema fields changedv0.3.20
    • addedInput schema / properties / description / anyOf
      Added value: +[
      +  {
      +    "type": "string"
      +  },
      +  {
      +    "type": "null"
      +  }
      +]
    • addedInput schema / properties / description / default
      Added value: +null
    • removedInput schema / properties / description / type
      Removed value: -"string"
    • removedInput schema / required
      Removed value: -[
      -  "description"
      -]
  2. First observedv0.3.3

TDQS

A4/5.0
Behavior4/5

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

Annotations are all false, so description must carry the transparency burden. It discloses that logs feed hebbrix_confidence, affecting future recommendations—a key side effect. It also explains the auto-fill shortcut behavior. It doesn't mention database persistence, overwrites, or other edge cases, but for a logging tool this is reasonable. No contradictions with 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 two short paragraphs: the first states the core purpose, the second provides a usage shortcut. It's front-loaded with the main purpose, and every sentence adds value. Slightly repetitive (mentions outcome twice) but overall efficient.

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 that annotations offer no hints (all false, though readOnly is correctly false as it's a write), the description does explain the side effect on hebbrix_confidence, which is important. It doesn't detail output or error conditions, but for a logging tool with output schema available, this is sufficient.

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. It mentions 'decision' and 'outcome' with allowed values (success | failure | partial) but does not explain the other parameters (collection_id, decision_type presumably). The shortcut hints at omitting description when outcome is provided, but doesn't clarify what each parameter contains or requiredness. The description under-explains the parameter semantics.

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 logs a decision and its outcome, with a specific verb (record) and resource (decision). It distinguishes itself from siblings like hebbrix_choose_action (which likely selects an action) and hebbrix_report_outcome (which may report results separately). The link to hebbrix_confidence adds purpose context.

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 explains the primary use case (logging decisions and outcomes to improve confidence) and provides a shortcut for logging right after a confidence check. It lacks explicit 'when not to use' or comparisons against alternatives like hebbrix_report_outcome, but the context is clear enough for most scenarios.

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

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Hebbrix/hebbrix-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server