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stevepridemore

Graph-Memory

Graph Entities

graph_entities
Read-only

Search or browse the entity catalog to check existence before creating, or list entities by type. Returns sorted results up to a specified limit.

Instructions

Browse or search the entity catalog. Use to check if an entity exists before creating one with graph_relate, or to list entities of a given type. For relationship-aware lookups (entity + its neighbors) use graph_query instead. Returns up to limit entities ordered by sort_by; pagination is single-page (raise limit if you need more).

Input Schema

NameRequiredDescriptionDefault
typeNoFilter by entity type (Person, Project, Concept, etc.)
limitNoMax results (default: 20)
searchNoFull-text search query
sort_byNoSort order (default: confidence)confidence
min_confidenceNoMin confidence threshold

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.2.2
  2. Removedv0.1.4
  3. Changed2 schema fields changedv1.0.1
    • addedInput schema / properties / limit / default
      Added value: +20
    • addedInput schema / properties / sort_by / default
      Added value: +"confidence"
  4. First observedv1.0.0

TDQS

A4.6/5.0
Behavior4/5

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

Annotations mark readOnlyHint=true. The description adds beyond this: 'Returns up to `limit` entities ordered by `sort_by`; pagination is single-page (raise `limit` if you need more).' This discloses return behavior and pagination constraint. No contradiction with annotations.

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, each purposeful. First sentence states purpose, second gives use cases and alternatives, third explains return behavior and pagination. No wasted words.

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?

No output schema, but description covers return behavior (up to limit entities, ordered) and pagination. Provides enough context for an agent to understand what the tool returns without needing an output schema. Minor omission: doesn't mention if count or metadata is included.

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 coverage is 100%, baseline 3. The description adds meaning by explaining `limit` and `sort_by` behavior ('returns up to limit entities ordered by sort_by') and clarifies `search` as full-text. This slightly exceeds baseline.

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 'Browse or search the entity catalog' and gives specific use cases: checking existence before creation and listing entities by type. It distinguishes from sibling tool graph_query by explicitly stating 'For relationship-aware lookups... use graph_query instead.'

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?

Provides explicit when-to-use (checking existence before graph_relate, listing entities) and when-not-to-use (relationship-aware lookups) with a named alternative (graph_query). This gives clear guidance for an AI agent.

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