Skip to main content
Glama

Auto-swap status

get_auto_swap

Check a game's auto-swap thumbnail settings and history: rotation schedule, QPTR-based replacement rules, and results of recent runs, including reasons for automatic disabling.

Instructions

Whether a game rotates its own thumbnails, on what schedule and rules, and what the last runs actually did. Auto-swap drops the worst-performing live thumbnails by QPTR and promotes replacements from the queue. A game that turned itself off reports why — that reason is the thing to act on.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gameYesGame name or universe id.
logsNoHow many past runs to include. Defaults to 5.
Behavior3/5

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

With no annotations, the description carries the full burden. It reveals that the tool reports why a game turned off, which is a behavioral outcome, but does not explicitly state that the operation is read-only or has no side effects. While the 'get' prefix suggests non-mutating behavior, the description does not confirm this or disclose any other traits (e.g., auth, rate limits).

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

Conciseness4/5

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

The description is three sentences and gets to the point immediately. Each sentence adds value: purpose, mechanism, and actionable advice. It is not overly verbose, though it could be trimmed slightly by not repeating the auto-swap definition if integrated elsewhere.

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?

Despite lacking an output schema, the description gives a solid overview of what information is returned (schedule, rules, last runs, reason if off). It provides enough context for an agent to know what to expect and how to act, and it fits coherently within the sibling tool ecosystem. Missing explicit field names or response format is acceptable given the absence of an output schema.

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%, so the schema already documents both 'game' and 'logs'. The description adds no additional meaning about the parameters; it only implies 'logs' relates to past runs, which is already in the schema. According to the rubric, a baseline of 3 is appropriate when schema handles the parameters.

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 clearly states the tool's purpose: retrieving auto-swap status including schedule, rules, and last run details, and explicitly distinguishes it from siblings like configure_auto_swap and run_auto_swap by focusing on status reporting. It uses a specific verb ('get') and resource ('auto-swap') and explains what the tool returns, making it unambiguous.

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?

The description implies usage context—that this is for checking status and acting on the reason if a game turned off—but does not explicitly state when to use it versus alternatives. It fails to mention that configure_auto_swap is for changes or run_auto_swap for triggering a run, leaving usage to inference.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Haydebug/whitehat-thumbnails-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server