Skip to main content
Glama

Traverse the Football Atlas knowledge graph

get_related
Read-onlyIdempotent

Graph neighbours of an object: outgoing and incoming relations, each with its relation type. Use this after get_entity to widen an answer with adjacent objects. It walks one hop from an id you already have — use search when you have a question and no starting object.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYesThe knowledge object to walk out from, by id.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
foundYes
incomingNo
outgoingNo
recoveryNo

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already cover readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is disclosed. The description adds valuable behavioral context by stating it walks exactly one hop and returns both outgoing and incoming relations. Edge cases like unknown ids or empty results are not mentioned, but the presence of an output schema mitigates that.

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 sentences with zero waste: the first states the core behavior, the second gives usage context and a route to an alternative. The most important information is front-loaded.

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?

For a one-parameter, read-only graph traversal tool with an output schema and safety annotations, the description covers the purpose, the one-hop scope, the typical call sequence (after get_entity), and the alternative when no starting object exists. Nothing essential is missing for an agent to select and invoke it correctly.

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 description coverage is 100% for the single 'id' parameter, giving the agent the necessary definition. The description adds extra semantic value by framing the id as one you already have from get_entity, implying it must be a known graph object and not a search string.

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 opening phrase 'Graph neighbours of an object' names a specific verb and resource, and specifies the scope as outgoing and incoming relations with their relation types. It also distinguishes from siblings by explicitly contrasting with get_entity ('after get_entity') and search ('use search when you have a question and no starting object').

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?

The description gives explicit when-to-use guidance: use after get_entity to widen an answer with adjacent objects, and use search instead when there is no starting object. This is a clear selection criterion among sibling tools.

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

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

A4.5/5.0
Disambiguation5/5

Every tool targets a distinct retrieval mode: answer for direct questions, search for candidate discovery, get_entity for a single object, get_related for graph neighbours, get_topic for tag browsing, get_latest for freshness, get_sources for citations, and get_overview for corpus-level context. The descriptions also explicitly contrast each tool with the alternatives that might be confused with it.

Naming Consistency4/5

The majority of tools follow a clear get_<noun> pattern (get_entity, get_topic, get_sources, get_overview, get_related, get_latest), and all names are lowercase snake_case. The two query actions, answer and search, break the get_ prefix pattern slightly, but they are intentionally different entry-point verbs rather than resource fetches.

Tool Count5/5

Eight tools is well within the ideal range for a knowledge-graph query server. Each tool covers a distinct aspect of corpus exploration without feeling redundant or bloated.

Completeness5/5

The server covers the full read-only workflow for a football knowledge atlas: corpus overview, freshness, full-text search, direct question answering, entity lookup, relation traversal, topic browsing, and source verification. Gaps like create/update/delete are not needed for this domain, and the descriptions deliberately handle misses with near-miss suggestions.