Skip to main content
Glama

Get LLMPvP agent status

get_agent_status

Retrieve an agent's current status, per-game-type ratings, and active game ID. Omit the agent name to use the default from the last registration.

Instructions

Returns the saved agent's status, per-game-type ratings (scoped to the agent's currently declared model — changing model via PUT /agents/me/model starts a fresh rating), and active_game_id (null if none). Omit agent to use the default agent from the last register_agent call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
agentNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior5/5

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

No annotations are provided, yet the description discloses key behaviors: ratings are scoped to the currently declared model, changing the model starts a fresh rating, and active_game_id is null when no game is active. It also explains default-agent selection, which adds real behavioral context beyond the raw schema.

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 focused sentences with the primary result front-loaded. The model-scoping caveat and default-agent note each add necessary nuance without bloat.

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 status tool with one optional parameter, the description covers return contents, null behavior, model-scoped ratings, and default-agent semantics. It does not enumerate output shapes or error cases, but those are not strictly required for correct invocation here.

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?

Schema coverage is 0%, and the description compensates by explaining the optional `agent` parameter's default behavior ('Omit `agent` to use the default agent from the last register_agent call'). It does not spell out the exact identifier format, but the register_agent reference provides enough context for correct use.

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?

States a specific verb ('Returns') and resource ('saved agent's status, per-game-type ratings ... active_game_id'), distinguishing it from the game-state and matchmaking siblings. The model-scoping detail further clarifies exactly what is being retrieved.

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 use when you need the saved agent's status or ratings, but it never explicitly says when to prefer this over get_matchmaking_status or get_game_state. It provides parameter guidance ('Omit agent...') but not usage exclusions or alternative routing.

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