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Aayat AI

Changelog ($0.005)

changelog
Read-only

What changed in a library or SDK since a date: every version published since then (npm, PyPI, crates, Go) and the release notes from its GitHub releases or CHANGELOG, newest first, with breaking-looking lines flagged. Works for any GitHub repository too (API SDKs, CLIs). Price: $0.005 in USDC per call (x402 or prepaid credits). In the free trial.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNoPackage name (e.g. openai, stripe, boto3).
repoNoOr: a GitHub repository, owner/name or URL.
sinceYesDate (YYYY-MM-DD or ISO time) to report changes after, up to 2 years back.
ecosystemNoPackage ecosystem: npm, pypi, crates (Rust) or go (Go modules).npm

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
sinceYes
latestNo
sourceNo
targetNo
changedYesTrue if anything was published after `since`.
omittedNo
releasesYesRelease notes since the date, newest first.
versionsYesPackage versions published since the date (registry).
fetchedAtNo
repositoryNo
breakingHintsYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.8/5.0
Behavior4/5

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

Annotations already declare readOnlyHint=true/openWorldHint=true, so safety is covered; the description adds genuinely useful behavior beyond that: newest-first ordering, breaking-line flagging, cross-ecosystem and GitHub-repo coverage, and the pricing/trial terms ($0.005 USDC via x402 or prepaid, free trial). It stops short of 5 by not noting limits such as the 'up to 2 years back' window that only appears in the schema.

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?

A single dense paragraph that front-loads the core capability before pricing and scope caveats. Every clause carries information, though the pricing/trial sentence could arguably be trimmed for an agent whose schema already implies commercial context.

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

Completeness5/5

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

An output schema exists, so return format needn't be explained, and annotations carry the safety profile. The description supplies the remaining essentials: sources, ordering, breaking-change flagging, GitHub fallback, and cost, making it complete for an agent to select and invoke it.

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 coverage is 100%, so the baseline is 3. The description reinforces the ecosystem list and the name-vs-repo dual input mode, but adds no format, syntax, or default guidance beyond what the schema's property descriptions already supply.

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 verb and resource: what changed in a library or SDK since a date, with the data sources enumerated (npm, PyPI, crates, Go plus GitHub releases/CHANGELOG). An agent immediately understands the output. It does not, however, distinguish itself from the very similar sibling package-changes, so it falls short of a 5.

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 through the data it assembles ('every version published since then... release notes... breaking-looking lines flagged') and the note that it also works for any GitHub repo, but there is no explicit when-to-use, when-not-to-use, or named alternative among siblings like package-changes or library-research.

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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