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by io.github.coret
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Comment Stats

get_comment_stats
Read-only

Comment count statistics

Returns the total number of validated comments made on records. When no archive_code is provided, the global total is returned. When an archive code is provided, the count for that archive is returned. Note: version 1.1 uses archive_code instead of archive.

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_comment_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault
archive_codeNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint and destructiveHint annotations, the description adds valuable behavioral context: it counts only 'validated' comments, states that no archive_code returns the global total, and includes a version note about parameter naming. This informs the agent about expected results and potential compatibility issues.

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 and front-loaded with the essential purpose, followed by two clear use-case scenarios and a version note. Every sentence adds value with no redundancy.

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 simple stats tool with one optional parameter, no output schema, and strong annotations, the description fully covers the tool's behavior. It explains the return value and the effect of the parameter, making it complete for an agent to invoke 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 schema provides no descriptions for archive_code (0% coverage), so the description carries the burden. It clearly explains the effect of providing or omitting archive_code, which compensates for the schema gap, though it does not specify the expected format or possible values for archive_code.

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?

The description clearly states the tool's purpose: returning the total number of validated comments made on records. It specifies the distinct global and archive-specific modes, which differentiates it from sibling stat tools like get_record_stats or get_event_type_stats.

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 description provides clear context on when to use the tool and how to use the optional archive_code parameter, explaining the two possible behaviors. It does not explicitly mention alternatives or when not to use, but the parameterized behavior is enough to guide an agent.

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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