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databutler-software-eol

Software support status

support_status
Read-onlyIdempotent

Whether a version of nodejs, python, ubuntu, debian, android, ios, macos, windows, oracle-jdk, go, ruby, php, postgresql, react is still supported, from a monthly snapshot of endoflife.date (340 release cycles, verified 2026-10-03). A version string resolves to its release cycle ("18", "18.19.0" and "v18" → Node.js 18; "3.11.4" → Python 3.11; "22.04.3" → Ubuntu 22.04; "bookworm" → Debian 12; "1.8.0_392" → Java 8; "11-24h2-w" → Windows 11 24H2 consumer). Returns supported true|false as of today, the eol date, days remaining or since end of life, active-support and extended-support end dates, LTS status, the latest release in the cycle, the newest supported (LTS) cycle, a plain-statement recommendation, and the endoflife.date page as source. "java" and "jdk" resolve to oracle-jdk; a version that fits several Windows editions comes back as candidates with each one's status; unknown products and versions answer with the nearest matches.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
productYesone of nodejs, python, ubuntu, debian, android, ios, macos, windows, oracle-jdk, go, ruby, php, postgresql, react (aliases: node, java, jdk, postgres, golang, osx, win)
versionYesa cycle ("18", "3.11", "22.04"), a full release ("18.19.0", "3.11.4"), a codename ("bookworm", "sonoma") or a Windows cycle id ("11-24h2-w")

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4/5.0
Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description goes well beyond them: it discloses the data provenance (monthly endoflife.date snapshot, 340 release cycles, verified 2026-10-03) and the exact ambiguity behavior ('candidates' for multi-edition Windows, 'nearest matches' for unknown input). That is substantive behavioral context for a no-output-schema tool.

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 core purpose, then dense but useful resolution and return detail in two long sentences. Slightly heavy on parenthetical examples, but nearly every clause carries information an agent needs.

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?

With no output schema, the description correctly enumerates the return payload (supported flag, eol date, days remaining, active/extended support, LTS, latest release, recommendation, source URL) and covers edge cases. The one gap is that it never positions itself against support_timeline.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds real meaning by showing how a version string resolves to a cycle ('18.19.0' and 'v18' → Node 18; '1.8.0_392' → Java 8; '11-24h2-w' → Windows 11 24H2 consumer), which the schema does not explain.

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 question ('whether a version of nodejs, python, ... is still supported') with an enumerated resource set and concrete resolution examples. It does not, however, differentiate itself from the sibling support_timeline, so an agent must infer the boundary between 'status now' and 'timeline'.

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 implied by the phrasing 'as of today', which suggests a point-in-time status check, but there is no explicit when-to-use, when-not-to-use, or named alternative (support_timeline). The alias and nearest-match notes help invocation but not tool selection.

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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