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

Beyond the readOnlyHint annotation, it discloses auth (none required), derivation (computed from registry publication dates), caching (one hour), and — crucially — coverage limits and exclusions (popular packages only, 0.x-to-0.y not reported as majors, calendar-versioned packages, pre-tracking deprecations). These constraints materially affect how an agent should interpret empty or partial results.

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

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

The purpose and scope are front-loaded, and the dense parenthetical enumerations each carry distinct, load-bearing information rather than filler. It is a long block of prose, which costs a little readability, but nearly every clause earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the full burden of describing the return shape, and it does so item by item (version at cutoff date, new majors with first release dates, latest version, upgrade-guide link, runtimes ending within 180 days, AI models with prices). Combined with the stated coverage caveats, an agent has everything needed to call and interpret this tool.

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

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

Schema description coverage is 100%, so cutoff format, limit bounds and the ecosystems enum are already fully documented in the schema. The description restates what is returned rather than adding parameter syntax or defaults beyond it, so the baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Returns what happened in software after a given date') and then enumerates exactly what is returned: new major versions across npm/PyPI/crates/Packagist, runtimes/frameworks released or ended, EOL windows, and AI model releases with prices. It explicitly distinguishes itself from sibling tools (upgrade_impact, package_status, eol_status) so an agent can route correctly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives explicit when-to-use ('once at the start of a coding session, passing the month your training data ends, or when you suspect a library you know has changed a lot') and names three alternatives with the conditions that select them. Nothing is left to inference.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.