Graph-Memory

Graph Contradictions

graph_contradictions

Read-only

Identify conflicting facts in your memory graph by detecting pairs connected by a CONTRADICTS edge. Use during reviews or before graph decay to surface unresolved contradictions.

Instructions

Find facts that contradict each other in the memory graph — pairs connected by a CONTRADICTS edge. Use during reviews, before a graph_decay run, or when the user asks about conflicting information. Returns {contradictions: [{node_a, node_b, description, detected_date, resolved}], count} ordered by most-recently detected. By default only unresolved pairs are surfaced; set include_resolved=true to audit historical resolutions. Resolve a contradiction by graph_weaken on the wrong edge or by graph_relate with relation=SUPERSEDES on the new fact.

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": "graph_contradictions"
  }
}

Input Schema

Name	Required	Description	Default
`include_resolved`	No	Include resolved contradictions (default: false)

Schema Changelog

Changes observed during successful MCP inspections.

Addedv0.2.2May 10, 2026
Removedv0.1.4May 9, 2026
Changed1 schema field changedv1.0.1May 7, 2026
- addedInput schema / properties / include_resolved / default
```
Added value: +false
```
First observedv1.0.0May 7, 2026

TDQS

A4.9/5.0

Behavior5/5

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

Annotations mark readOnlyHint=true, and description aligns by specifying it returns contradictions without mutations. Adds details on return format and default filtering of unresolved pairs.

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?

Two well-structured sentences: purpose, usage, return format, parameter guidance. No redundant words.

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

Completeness5/5

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

With simple schema (1 param, no output schema), description fully covers purpose, usage, return structure, parameter semantics, and resolution hints.

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?

Schema covers parameter with description. Description adds context: explains default behavior and when to use include_resolved=true (historical audits), building on schema.

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?

Clearly states the tool finds contradictory facts via CONTRADICTS edges. Distinct from sibling tools like graph_audit or graph_search by focusing on contradictions.

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

Usage Guidelines5/5

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

Explicitly states when to use: during reviews, before graph_decay, or when user asks about conflicts. Also suggests resolution tools (graph_weaken, graph_relate) as alternatives.

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