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game_settings

Retrieve current public game settings from the Splinterlands API, with results cached for one hour per exact query.

Instructions

Read current public settings from the API, cached for one hour per exact query. Matching version and config_version still returned the full settings body; they are not a delta protocol. The server never transcribes configuration constants into this tool. Uses a bounded success cache keyed by exact supplied query, otherwise makes one logical GET request Does not auto-fetch continuation pages. Required inputs reflect tool policy as well as measured upstream requirements. Other declared filters are forwarded as supplied; their effectiveness is not implied by the schema. Array responses are locally limited to 100 rows and 256 KiB, with truncation reported in text and metadata. Oversized records are refused without partial fields.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
versionNo
config_versionNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.0

TDQS

A3.8/5.0
Behavior5/5

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

With no annotations at all, the description carries the full burden and does an excellent job. It discloses caching duration, non-delta behavior, bounded cache mechanics, request method, pagination handling, filter forwarding caveats, array size limits, truncation reporting, and oversized-record refusal. This is far beyond typical descriptions and gives an agent a realistic model of the tool's behavior.

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

Conciseness3/5

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

The description is dense and information-rich, but it includes boilerplate like 'Required inputs reflect tool policy as well as measured upstream requirements' which adds little and could confuse given there are no required parameters. It is structured around behaviors but could be trimmed without losing essential information.

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

Completeness4/5

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

For a simple read tool with two optional params and no output schema, this description covers most operational aspects: caching, request pattern, pagination, limits, and error behavior. It mentions the response is the 'full settings body'. The main gap is the lack of clear parameter value guidance and response structure, but overall it is sufficiently complete for an agent to invoke correctly.

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 coverage is 0%, so the description must compensate. It adds the key fact that version and config_version do not trigger a delta response—they still return the full body. It also notes that filters are forwarded without effectiveness guarantees. However, it never explains what these parameters semantically represent, what formats are expected, or what happens when they are omitted. Some value is added, but significant ambiguity remains.

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 opens with 'Read current public settings from the API', which names a specific verb and resource, making the core purpose clear. It does not explicitly contrast with sibling tools like purchase_settings or game_maintenance, so it stops short of full differentiation in the same space.

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

Usage Guidelines3/5

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

Usage is implied by the purpose: call this when you need current public settings. However, there is no explicit guidance on when to prefer this over alternatives, when not to use it, or conditions that would make another tool more appropriate. The caching/behavior details add context but not decision rules.

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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