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ai-dememory

ai-dememory

by GonzaloTorreras
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

Review False Positives

memory.review_false_positives
Read-only

Review secret-scan false positives by retrieving deterministic review IDs and suppression metadata for efficient triage.

Instructions

Return secret-scan findings with deterministic review ids and suppression metadata.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "memory.review_false_positives"
  }
}

Input Schema

NameRequiredDescriptionDefault
due_onlyNo

Output Schema

NameRequiredDescriptionDefault
policyYes
enabledYes
due_onlyYes
findingsYes
returned_countYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.0.0

TDQS

A3.6/5.0
Behavior3/5

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

Annotations declare readOnlyHint=true and destructiveHint=false, so the description adds limited behavioral context by mentioning deterministic review ids and suppression metadata. However, it does not detail rate limits, pagination, or other behaviors beyond what annotations provide.

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 one sentence, concise, and front-loaded with the core purpose. No unnecessary words, and it effectively conveys the main action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present, return values need not be explained. However, the description omits documentation of the 'due_only' parameter, leaving the agent uninformed about its purpose. This gap reduces completeness for a simple tool.

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%, yet the description does not mention the only parameter 'due_only'. The description fails to add any meaning about parameters, which is a significant gap for a tool with a single parameter.

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 returns secret-scan findings with specific metadata, distinguishing it from sibling tools like memory.review_stale_false_positives. The verb 'return' and resource 'secret-scan findings' are specific and unambiguous.

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 usage for reviewing false positives but does not provide explicit guidance on when to use this tool versus alternatives like memory.review_stale_false_positives or memory.review_recommendations. No when-not-to-use or context for selection.

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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