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Count archived items

get_archive_counts
Read-only

Get the count of archived items per type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNoHow many archived items there are, keyed by archive type.
successYesTrue when the call succeeded. A failure comes back as an error result instead.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
      +  "$schema": "http://json-schema.org/draft-07/schema#",
      +  "additionalProperties": false,
      +  "properties": {
      +    "data": {
      +      "additionalProperties": {},
      +      "description": "How many archived items there are, keyed by archive type.",
      +      "type": "object"
      +    },
      +    "success": {
      +      "description": "True when the call succeeded. A failure comes back as an error result instead.",
      +      "type": "boolean"
      +    }
      +  },
      +  "required": [
      +    "success"
      +  ],
      +  "type": "object"
      +}
  2. First observed

TDQS

A3.8/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds that the operation returns counts grouped by type, which is mildly useful beyond the annotations. No contradiction or hidden behavior is disclosed, but there is also no extra depth about pagination, limits, or which types are counted.

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?

A single, front-loaded sentence with no filler. Every word earns its place, and the key concepts ('count', 'archived items', 'per type') appear immediately.

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?

Given the tool's simplicity—no parameters, an output schema present, and annotations covering read-only safety—the description is complete enough for an agent to select and invoke the tool correctly. Nothing essential is missing.

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 has zero parameters and the schema coverage is 100%, so there is nothing for the description to clarify about arguments. Per the baseline for zero-param tools, this is sufficient.

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?

The description uses a specific verb ('Get') and a clear resource ('count of archived items per type'). It is easy to tell apart from sibling count tools like count_clients or count_unread_notifications, though it does not explicitly contrast itself with list_archive or other archive-related tools.

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 when to use it: when you need aggregate counts of archived items by type. However, it never explicitly states that this tool should be used over list_archive (which likely returns details) or other count tools. Usage guidance is present only by implication, not by explicit direction.

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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