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stevepridemore

Graph-Memory

Graph Merge Suggestions

graph_merge_suggestions
Read-onlyIdempotent

Identifies potential duplicate entity pairs by combining embedding similarity, shared neighbor overlap, and name token Jaccard. Use to review and triage entity consolidation before merging.

Instructions

Surface candidate pairs of entities likely to be duplicates. Read-only — never auto-merges. Combines embedding similarity, shared-neighbor overlap, and name-token Jaccard. Same-type only. Use to triage entity-explosion before running graph_merge (destructive consolidation) or graph_relate with ALIAS_OF (soft alias).

Input Schema

NameRequiredDescriptionDefault
limitNoMax suggestions to return (default 20, max 100)
weightsNoOverride default weights (0.4 / 0.4 / 0.2)
entity_idNoScope to one entity's potential duplicates
min_scoreNoCombined-score threshold to surface (default 0.8)
entity_typeNoScope to one entity type (Person, Project, etc.)
log_to_auditNoEmit merge_flagged audit events for surfaced pairs (default true)
min_embedding_similarityNoEmbedding-similarity floor for candidates (default 0.85)

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.2
  2. Removedv0.1.4
  3. First observedv1.0.0

TDQS

A4.6/5.0
Behavior5/5

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

Annotations already indicate read-only and non-destructive. The description adds 'never auto-merges' and details the algorithm (embedding similarity, shared-neighbor overlap, name-token Jaccard). No contradictions.

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 sentences: purpose, read-only and algorithm, usage guidance. Every sentence provides essential information with no redundancy. Ideal conciseness for an AI agent.

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 suggestion tool without output schema, the description covers purpose, safety, algorithm, and usage. Minor gap: does not describe return format (likely a list of pairs). But given the clarity and annotations, it is nearly complete.

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 coverage is 100% with detailed descriptions for all 7 parameters. The description provides high-level context (e.g., default weights) but does not add significant meaning beyond the schema. Baseline 3 is appropriate.

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 verb 'surface' and the resource 'candidate pairs of entities likely to be duplicates'. It distinguishes from siblings like graph_merge (destructive) and graph_relate (soft alias) by mentioning alternative uses.

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 advises using this tool for triaging entity-explosion before other specific operations, naming alternatives (graph_merge, graph_relate). Provides clear when-to-use and context.

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