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upgrade_check

What changed in a package since the version your code targets: breaking changes, deprecations, security fixes and major versions crossed, with the sentence that triggered each label. Call this before writing code against a library you may know only from older training data. Costs $0.01 (x402, USDC).

Input Schema

NameRequiredDescriptionDefault
fromYesVersion your code targets, e.g. 14.2.0
packageYesPackage name (npm/PyPI) or source id, e.g. next, openai, node

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations supplied, the description carries the full disclosure burden, and it does surface two genuinely useful behaviors: the response includes the source sentence behind each label, and the call costs $0.01 via x402/USDC. The payment requirement is the kind of detail an agent cannot get from structured fields and is well worth stating. It stops short of describing failure modes, what happens for unknown packages or versions, or whether results are cached, which matters for a paid call.

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?

Three sentences, front-loaded with the payoff, then the when-to-use trigger, then the cost. Every sentence carries distinct information with no filler. Slightly dense in the first sentence, but nothing is wasted.

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?

For a two-parameter read tool with no output schema and no annotations, the description covers what it returns, when to call it, and its pricing. The main omission is any routing guidance relative to the four sibling tools, several of which appear to overlap in scope.

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?

Schema description coverage is 100%, so both 'package' and 'from' are already documented with examples in the schema. The description reinforces 'the version your code targets' for 'from' but adds no format, range, or validation detail beyond what is structured. Baseline 3 applies when the schema does the heavy lifting.

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?

The description names a specific resource and scope: 'What changed in a package since the version your code targets,' and enumerates the categories returned (breaking changes, deprecations, security fixes, major versions crossed) plus the evidence format ('the sentence that triggered each label'). That is far more than a restatement of the name. It does not, however, distinguish itself from the overlapping sibling 'get_changes' or 'preview_changes', so an agent must guess at the boundary.

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?

'Call this before writing code against a library you may know only from older training data' gives a concrete triggering condition, which is strong positive guidance. There are no exclusions and no reference to the sibling tools, so the agent gets no signal about when a cheaper alternative like preview_changes or digest would be preferred.

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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