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Glama
BK927
by BK927

ow_esports

Read-onlyIdempotent

Retrieve Overwatch Champions Series Korea match data, hero meta, bans, and team stats with filters for map, hero, and date range.

Instructions

Read the released OWCS Korea dataset with match coverage and release dates. Esports metrics are separate from ranked ladder statistics.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
mapNo
heroNo
teamNo
viewNohero_meta
afterNo
limitNo
stageNo
beforeNo
regionNoKOREA

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.1.0

TDQS

B3.1/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false, and the description's use of 'Read' is consistent with those hints. The description adds useful context about the dataset's scope (esports vs. ranked ladder) without contradicting the annotations, but it does not introduce any additional behavioral caveats, 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?

The description is exceptionally concise, consisting of two short sentences that convey the core purpose and scope without unnecessary detail or repetition. It is well-structured and front-loaded, making it easy to parse quickly.

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?

Given the tool has 9 parameters, a date range, a limit, and an enum, the description is notably incomplete. It does not explain what the response contains, how pagination works, or what the various filters mean. The output schema exists but is not described, and the description's mention of 'match coverage and release dates' is too vague to cover the full functionality.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters1/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has 0% description coverage, and the tool description does not explain any of the 9 parameters (e.g., map, hero, team, view, after, before, limit, stage, region). While the view enum values are somewhat self-explanatory, the description fails to compensate for the complete lack of parameter documentation, so it provides no meaningful guidance on parameter usage.

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 clearly states that the tool reads the OWCS Korea dataset, and it distinguishes esports metrics from ranked ladder statistics, which clarifies its specific resource and scope. However, it does not explicitly name the kind of data returned (e.g., matches, teams, maps) beyond vague mention of 'match coverage and release dates', so it falls short of a perfect 5.

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?

The description offers only implicit guidance by noting that esports metrics are separate from ranked ladder statistics, but it does not explicitly state when to use this tool versus sibling tools such as search endpoints or catalog/status tools. There is no clear 'use this for X, use that for Y' instruction, leaving the selection criteria largely to inference.

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