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Glama

Overview of Football Atlas

get_overview
Read-onlyIdempotent

Corpus overview: what this instance knows, counts by type, published tags, freshness. Use this first when you land here and do not yet know whether this corpus can answer your question.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagsYes
by_typeYes
instanceYes
descriptionYes
total_mediaYes
total_objectsYes
newest_verificationYes
oldest_verificationYes

TDQS

A4.2/5.0
Behavior4/5

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

Annotations already declare readOnly, non-destructive, idempotent behavior. The description adds useful context about what the overview exposes (counts by type, published tags, freshness) and frames it as a triage tool. It does not repeat annotation information, and there is no contradiction.

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 concise sentences that front-load the core purpose and then give practical usage guidance. Every word earns its place; no filler or redundancy.

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 parameterless metadata inspection tool with output schema and safety annotations, the description fully covers purpose, contents, and when to use it. Nothing essential is missing.

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?

The tool has zero parameters, so the baseline is 4. The description does not need to explain parameter meaning, and the output schema covers the return structure.

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?

Description states it provides a corpus overview with counts by type, published tags, and freshness. It clearly identifies the resource (the corpus) and what it reveals, though it uses a noun phrase rather than an explicit verb+resource structure. It is sufficiently distinct from siblings like search and get_entity by being the high-level entry point.

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

Usage Guidelines4/5

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

Explicitly instructs to use this tool first when arriving and before knowing whether the corpus can answer the question. This provides strong placement guidance among siblings, though it does not explicitly name alternatives or state when not to use it.

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

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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.