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chatgenius-mcp

chatgenius-mcp

Official
by SumCodeAI

get_knowledge_usage

Read-onlyIdempotent

Retrieve knowledge base usage to see item counts against plan limits by FAQs, services, and documents, plus document storage; check can_add before creating.

Instructions

Get knowledge base usage. How many items exist against the plan cap, broken down by FAQs, services and documents, plus document storage. Check can_add before creating.

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.2

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description adds value beyond that by disclosing the shape of the result (counts vs plan cap, per-category breakdown, storage) and its role as a gating check before creation. No auth or rate-limit context, but that is minor for a read-only usage endpoint.

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?

Three short sentences, front-loaded with the purpose, then the return contents, then the actionable workflow hint. No filler or redundancy.

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?

There is no output schema, so the description carries the burden of explaining return values, and it does so adequately by naming the counts, breakdown and storage figure. It could be slightly richer (e.g. whether the cap is a hard limit or what happens at 100%), but an agent has enough to call it correctly.

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?

The tool takes zero parameters, so there is nothing for the description to disambiguate; the baseline for a parameterless tool applies. The description correctly implies no filtering or scoping inputs are needed.

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 and resource ('Get knowledge base usage') and then enumerates exactly what is returned: item counts against the plan cap broken down by FAQs, services and documents, plus document storage. This clearly separates it from listing siblings like list_faqs or list_documents, though it doesn't name those siblings explicitly.

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?

The closing sentence 'Check can_add before creating' gives a concrete pre-flight workflow, which is real when-to-use guidance. It stops short of stating when not to use it or naming a direct alternative, so it falls just short of a 5.

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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