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apidrift

get_apidrift_info

Get pricing and details for APIDrift: weekly plus same-day urgent email alerts tracking deprecations, breaking schema changes, and pricing shifts across OpenAI, Anthropic, Google, xAI, Together, Mistral, Groq, Cloudflare Workers AI, and AWS Bedrock. Useful for an agent helping an engineering team that depends on LLM provider APIs avoid getting blindsided by an upstream breaking change.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior3/5

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

No annotations are provided, so the description carries the behavioral disclosure burden. The verb 'Get' and the phrase 'pricing and details' imply a read-only informational operation, and the description explains the kind of information returned. However, it does not disclose potential side effects, authentication requirements, rate limits, or any return structure, which keeps this at the minimum viable level.

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 two sentences with no filler. The first sentence front-loads the core action and the full scope of details, while the second sentence adds practical usage context. Every clause earns its place, and the length is proportionate to the tool's simplicity.

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 zero-parameter informational tool with no output schema, the description is nearly complete: it states the subject, the content areas covered, the providers included, and the real-world use case. It stops short of describing the exact return format, but for this simple tool the provided detail is sufficient for an agent to select and invoke it correctly.

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 has zero parameters, so the input schema requires no parameter documentation. The baseline of 4 applies, and the description does not need to add parameter-level meaning. It correctly omits any irrelevant parameter discussion.

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 begins with a specific verb ('Get') and a clear resource ('APIDrift'), then enumerates exactly what is covered: pricing, alerts, deprecations, breaking schema changes, and pricing shifts across a named list of providers. There are no sibling tools, so no differentiation is needed, and the purpose is unambiguous.

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 explicitly states when the tool is useful: when an agent is helping an engineering team that depends on LLM provider APIs and needs to avoid being blindsided by upstream breaking changes. There are no alternatives or exclusions to mention because there are no sibling tools, so this is clear and appropriately scoped.

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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