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Algenta MCP Server

by io.github.thyn-ai
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get_limits

Read-onlyIdempotent

Get current plan quotas and limits for the active API key. Read-only and non-destructive; not separately rate-limited. Use get_usage for current consumption against these limits. Returns the plan's quota ceilings, including rate, concurrency, storage, and LLM spend cap.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_limits"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false; the description restates 'Read-only and non-destructive' (redundant) but adds valuable context beyond annotations: 'not separately rate-limited' and the specific return fields ('rate, concurrency, storage, and LLM spend cap'). This adds behavioral and output detail beyond the structured metadata.

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 compact, front-loaded with the purpose, and every sentence earns its place: purpose, safety/rate-limit note, sibling routing, and return contents. No fluff or repetition beyond the harmless restatement of read-only/non-destructive.

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

Completeness5/5

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

For a no-parameter, read-only tool with no output schema, the description covers all necessary information: what it does, how it relates to get_usage, rate-limit behavior, and the structure of the returned data. Nothing an agent needs to call it correctly is missing.

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

Parameters5/5

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

The tool has zero parameters, so the baseline is 4. The description goes beyond by detailing exactly what the tool returns ('quota ceilings, including rate, concurrency, storage, and LLM spend cap'), which fully compensates for the lack of an output schema and gives agents a complete picture of the result semantics.

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 and resource ('Get current plan quotas and limits for the active API key') and explicitly differentiates from the sibling get_usage by naming it as the consumption counterpart. The purpose is unambiguous and distinguishes the tool from many other get_* siblings.

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

Usage Guidelines5/5

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

Explicitly names the alternative tool (get_usage) and the condition for using it ('current consumption against these limits'). Also notes that this tool is 'not separately rate-limited,' which is a practical usage consideration. This gives clear guidance on when to call this tool versus alternatives.

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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