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Glama

Browse Football Atlas by topic

get_topic
Read-onlyIdempotent

List the knowledge objects carrying a tag (topics are content-backed tags). Use this to browse a known topic; use search when you have a question rather than a tag, and get_overview to see which tags exist. An unknown tag comes back with the topics that do exist, so a miss still moves you forward.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagYesThe topic to list, spelled exactly as get_overview publishes it. Every published topic has objects under it, so an empty answer means the topic does not exist.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagYes
totalYes
resultsYes
recoveryNo

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive, and closed-world behavior, so the safety burden is covered. The description adds real behavioral value on top: the semantics of topics as content-backed tags and the graceful miss behavior ('an unknown tag comes back with the topics that do exist'), which an agent could not infer from annotations alone. It stops short of disclosing result ordering or pagination, but the output schema covers return shape, so a 4 is appropriate.

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, zero waste: the core action is front-loaded, the routing guidance follows, and the edge-case behavior closes it out. Every sentence carries distinct information, and none repeats the schema or annotations.

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 single-parameter, read-only browse tool, the description plus annotations and output schema cover everything an agent needs: what it does, when to use it, what an unknown tag yields, and how to phrase the tag. Return values are covered by the output schema, so the description need not explain them. No meaningful gap remains.

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%, and the schema itself is exemplary: it specifies exact spelling as published by get_overview and states that an empty answer means the topic does not exist. The description only adds marginal param-level meaning ('content-backed tags'), which reinforces rather than extends the schema. Per the baseline rule for high coverage, a 3 is correct.

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 names a specific verb and resource ('List the knowledge objects carrying a tag') and clarifies the semantics ('topics are content-backed tags'). It also differentiates from siblings by naming search and get_overview as the alternatives for different intents, so an agent can distinguish this tool without opening schemas.

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?

Explicit routing is given: browse a known topic here, use search for a question rather than a tag, and use get_overview to discover which tags exist. The description also covers the edge case of an unknown tag and why it is still productive, leaving no ambiguity about when to invoke this tool versus its siblings.

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.