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Kiln

Kiln

by codeofaxel
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python

community_stats

Read-only

Retrieve local print-registry totals—records, models, printers, materials, and success rate—plus shared community pool counts, with local stats available offline.

Instructions

Get overall print-registry statistics.

        ``stats`` covers this install: total records, unique models,
        printers, materials, and overall success rate.  ``community``
        adds the size of the shared pool everyone contributes to —
        counts only, available to anyone signed in.

        Works offline: the local numbers are always returned.

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": "community_stats"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already establish readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so safety is covered. The description adds real behavioral context beyond that: the call works offline, local figures are always returned, and the community pool is counts only and gated on being signed in. It does not address caching or freshness of the numbers.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the purpose, then a compact breakdown of the two result groups, then the offline guarantee. The ``stats``/``community`` tokens are ambiguous — an agent could read them as modes rather than response sections — which is the main structural weakness in an otherwise tight definition.

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?

With no output schema present, the description takes on the job of describing return values and does so: it names the specific metrics in each group and states what is always available. For a zero-parameter, read-only stats call there is little else an agent needs before invoking it.

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 no parameters, so the schema defines nothing to interpret and the baseline is 4. The description wisely spends its space on what the empty-argument call returns instead of on absent inputs.

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 overall print-registry statistics") and enumerates the contents: total records, unique models, printers, materials, success rate, plus community pool size. It does not differentiate itself from nearby siblings such as printer_stats, usage_summary, or get_community_insight, so it is clear on what it does but not on how it differs.

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?

Usage is only implied — an agent infers it should call this when it wants aggregate registry numbers rather than per-printer or per-session data. There is no explicit when-to-use statement, no exclusion of alternatives, and no guidance on calling it alongside printer_stats or usage_summary.

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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