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PyModel
by PyModel

agy_status

Check bridge token spend, quota cooldowns, in-flight runs, model chains, warm sessions, agy version and flags, and available models before large fan-outs or set_model calls.

Instructions

What this bridge has spent and what it can still do: tokens by model, live quota cooldowns, runs in flight, the resolved model chain per tool, the user's set_model choice, the models agy offers, warm sessions, and the agy version and flags detected at startup. Check this before a large fan-out, or to list models before set_model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv2.1.0

TDQS

A3.6/5.0
Behavior3/5

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

No annotations provided, so description carries full burden. It discloses what the tool returns and hints at read-only nature ('what this bridge has spent', 'what it can still do'), implying a safe status check. However, it doesn't state whether it has side effects, requires auth, or is idempotent. The informational verbs strongly imply read-only but leave room for ambiguity.

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 first sentence is a dense list of returned data that, while informative, is long and somewhat run-on. The second sentence gives usage guidance clearly. The description front-loads the purpose but the enumeration could be tightened; every item earns its place by describing the return payload, but structure could be improved.

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

Completeness3/5

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

For a zero-param status tool with no annotations and no output schema, the description does a good job listing what is returned, compensating for the lack of output schema. However, it doesn't disclose safety profile (read-only status), potential side effects, or failure modes. Given no annotations, more behavioral disclosure would be expected.

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?

Zero parameters, so baseline is 4 by rule. Description doesn't need to explain parameter semantics.

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?

States a specific verb (reports/spends) and resource (bridge status) with a detailed enumeration of what is returned: tokens, quotas, runs, model chain, set_model choice, etc. Distinguishes itself from siblings like set_model and delegate, though it doesn't explicitly name a sibling to compare against.

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

Usage Guidelines4/5

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

Provides clear when-to-use guidance: 'Check this before a large fan-out, or to list models before set_model.' This gives two concrete triggers and references a sibling for model listing. No explicit exclusions, but the context is well-defined.

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