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CodeAbra

iai-personal-memory-engine

memory_reinforce

Idempotent

Strengthen associations among records retrieved together by incrementing their connection weights, so co-used records appear together in future context.

Instructions

Boost Hebbian edges among co-retrieved record ids. Mutates edge weights. Use when two records co-answered.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idsYesRecord UUIDs that were co-retrieved in the current context. Edges between every pair are incremented; identical pair sets are idempotent within one session.
session_idNoSession identifier for correlating this reinforcement with the session's retrieval history. Optional; omit for old clients.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
new_weightsNo
edges_boostedNo

Schema Changelog

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

  1. Changed1 schema field changedv3.1.0
    • addedInput schema / properties / session_id
      Added value: +{
      +  "description": "Session identifier for correlating this reinforcement with the session's retrieval history. Optional; omit for old clients.",
      +  "type": "string"
      +}
  2. Addedv3.0.0
  3. Removedv2.6.1
  4. Changed2 schema fields changedv0.2.0
    • changedInput schema / properties / ids / description
      Previous value: -"Record UUIDs that were co-retrieved in the current context."New value: +"Record UUIDs that were co-retrieved in the current context. Edges between every pair are incremented; identical pair sets are idempotent within one session."
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "properties": {
      +    "edges_boosted": {
      +      "type": "integer"
      +    },
      +    "new_weights": {
      +      "additionalProperties": {
      +        "type": "number"
      +      },
      +      "type": "object"
      +    }
      +  },
      +  "type": "object"
      +}
  5. First observedv1.0.0

TDQS

A4.2/5.0
Behavior4/5

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

The description discloses the mutation semantics ('Mutates edge weights') and reinforces the Hebbian reinforcement idea, which adds detail beyond the readOnlyHint=false annotation. It does not contradict the annotations; idempotency is already declared in the schema and annotation.

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?

Three short, meaningful sentences: the action, the mutation effect, and the usage condition. No fluff or repetition that wastes tokens.

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 simple two-parameter tool with an output schema and annotations, the description plus schema provide enough to invoke it correctly. It could be more explicit about when not to use it relative to memory_recall or memory_consolidate, but this is not a critical gap.

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

Parameters3/5

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

Schema description coverage is 100%, so the baseline is 3. The description adds only contextual meaning to 'ids' via 'co-retrieved record ids' but does not add parameter-level details that the schema already lacks.

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 uses a specific verb ('Boost') with a clear resource ('Hebbian edges among co-retrieved record ids') and states the core effect ('Mutates edge weights'). It distinguishes this from sibling memory tools by focusing on edge-weight reinforcement rather than search, capture, or recall.

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?

It explicitly says 'Use when two records co-answered', giving a clear trigger condition. It does not name exclusions or alternative sibling tools, so it does not fully meet the 5-level bar.

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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