version-truth

Get Product

get_product

Read-onlyIdempotent

All release cycles for a product, newest first: latest patch version, release date, LTS status/date, end-of-life date, and end of active support. Answers: what is the CURRENT version of X? Which major versions are still supported? When does version Y reach EOL? Use exact slugs from list_products (e.g. nodejs, python, django, postgresql, ubuntu, amazon-eks).

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "product": "<product>"
    },
    "name": "get_product"
  }
}

Input Schema

Name	Required	Description	Default
`product`	Yes	Product slug from list_products, e.g. 'nodejs', 'python', 'react', 'postgresql'

Schema Changelog

Changes observed during successful MCP inspections.

First observedAug 20, 2026

TDQS

A4.2/5.0

Behavior4/5

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

Annotations already establish this as a safe read-only, idempotent operation. The description adds valuable behavioral context by specifying ordering (newest first) and the exact data fields returned. It does not discuss pagination or response envelope, but for this simple tool the added transparency is solid.

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, front-loaded with the core behavior, and every sentence serves a purpose: first explains output, second lists use cases and input guidance. There is no filler or repetition beyond acceptable reinforcement of the slug requirement.

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 compensates by listing key fields, ordering, and the questions it answers. It is complete enough to invoke correctly and interpret results for common versioning/EOL tasks, though it could be slightly richer about the exact response structure or pagination.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already fully describes the product parameter as a slug from list_products with examples, so the description adds little new semantic value beyond a few extra examples and emphasis on exact slugs. This meets the baseline for high schema coverage without meaningfully extending it.

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 returns all release cycles for a product, newest first, with specific fields like latest patch version, LTS status, and EOL date. It also lists concrete question types it answers, which distinguishes it from siblings like list_products and get_cycle.

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 use cases, such as finding the current version or EOL date, and explicitly instructs the agent to use exact slugs from list_products with examples. It does not explicitly contrast with get_cycle, so it lacks an exclusion clause for that sibling, but the guidance is still strong.

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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