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memoryguard_semantic_check

Check incoming text against stored memories to detect semantic duplicates or conflicts, including paraphrases and cross-lingual matches, and retrieve similar memories with similarity scores.

Instructions

Check a new text against existing memories for semantic duplicates/conflicts (cross-lingual, paraphrase). Returns similar memories with similarity scores. Read-only.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
kindNooptional kind of the new memory, used for conflict detection
textYesnew text to check
thresholdNosimilarity threshold (default: 0.85)
workspaceNoworkspace path (default: .)
share_group_idNoshare group ID (default: default)

Schema Changelog

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

  1. First observedv0.7.8

TDQS

A4/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and it does disclose a key behavioral trait: 'Read-only.' It also communicates what the tool returns (similar memories with similarity scores) and its cross-lingual/paraphrase behavior. This is solid context, though it could mention edge cases like empty results or threshold effects.

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 two sentences with no filler. It front-loads the core action, adds useful parenthetical detail, states the return value, and ends with a clear safety qualifier. Every word 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?

The schema covers all parameters, the description explains the return value despite lacking an output schema, and the read-only nature is disclosed. It is complete enough for an agent to call safely and understand the result, though a brief note on when to use it (e.g., before writing a memory) would make it fully self-contained.

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 minimal parameter meaning beyond the schema, mainly rephrasing 'text' as 'new text'. It does not explain threshold, kind, workspace, or share_group_id beyond what the schema already provides.

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 states a specific action ('Check'), a specific resource ('new text against existing memories'), and the purpose ('semantic duplicates/conflicts'). It also explicitly notes cross-lingual and paraphrase matching, which clearly sets this apart from a generic memory search or read tool.

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 implies this is for checking new text before committing it as a memory, but it does not explicitly say 'use before memory_write' or contrast with alternatives like memoryguard_memory_search. Usage context is inferable but not stated.

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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