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Glama

trawl_search_relationships

Search relationships between entities in a knowledge graph, with filters for relationship type and traversal depth up to 4 hops.

Instructions

Search for relationships between entities in the knowledge graph.

Input Schema

NameRequiredDescriptionDefault
entityYesEntity to find relationships for
max_hopsNoMax traversal depth (default: 2, max: 4)
pool_nameNoPool name
relationship_typeNoFilter by relationship type

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.4.1

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It says nothing about whether the entity must already exist, whether the operation is read-only, how traversal cost scales with max_hops, or what the result contains — all important for a multi-hop graph traversal.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

A single front-loaded sentence with zero redundant content. It is efficient, though its brevity comes at the cost of the missing detail noted elsewhere.

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

Completeness2/5

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

With four parameters, no output schema, and no annotations, the description should explain traversal depth implications, how relationship_type narrows results, and what a pool scopes. None of that is present, leaving the agent to infer behavior from schema field names alone.

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 every parameter (entity, max_hops, pool_name, relationship_type) is already documented in the schema, including defaults and limits. The description adds no meaning beyond that, which is the baseline 3 case.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description names a specific verb ('Search') and resource ('relationships between entities in the knowledge graph'), which is clearly distinct from entity search or graph statistics. It does not, however, distinguish itself from adjacent graph tools like trawl_build_graph, trawl_graph_stats, or trawl_graph_export beyond the word 'search'.

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

Usage Guidelines2/5

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

There is no guidance on when to use this versus trawl_search_entities or trawl_search_pool, and no prerequisite conditions (e.g., whether a graph must be built first). Usage is only implied by the verb.

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