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Get Release Summary

get_release_summary

Combine commits, pull requests, linked issues, and contributor statistics between two Git tags to produce a structured release context ready for AI release-note synthesis.

Instructions

Generate a structured release context object ready for AI synthesis into release notes. Combines commit data, PR metadata, linked issues, contributor list, and aggregate statistics for the range between two tags.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
repoYesGitHub repository name
ownerYesGitHub repository owner (user or organization)
to_tagYesThe new release tag or HEAD (head / newer ref)
from_tagYesThe previous release tag (base / older ref)
Install Server

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It transparently describes behavior by listing what data the tool combines and clarifying that the output is a structured object intended for synthesis. It does not discuss side effects, rate limits, or edge cases, but 'Generate' and the aggregation wording sufficiently signal a read-only, non-destructive operation.

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 a single sentence with no wasted words. It front-loads the core purpose and then efficiently enumerates the combined data sources, giving the agent maximum signal per word.

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?

There is no output schema, but the description compensates by naming the output type and its major components. The four required parameters are fully covered by the schema. Some detail about output shape or edge cases is absent, but the description is complete enough for an agent to select and invoke the tool effectively.

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 adds only the 'range between two tags' framing, which reinforces from_tag and to_tag semantics but does not meaningfully expand on what the schema already documents for owner, repo, from_tag, or to_tag.

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 names a specific verb ('Generate'), a specific resource ('structured release context object'), and the scope ('range between two tags'). It also lists concrete contents (commit data, PR metadata, linked issues, contributors, aggregate statistics), which clearly distinguishes it from sibling tools focused on individual data types.

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 phrase 'ready for AI synthesis into release notes' gives a clear context for when to use the tool. It does not explicitly name sibling alternatives or state when not to use them, but the 'Combines...' clause implies that this is the aggregate choice when multiple data sources are needed.

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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