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saidsef

GitHub PR Issue Analyser

by saidsef

Github Reply To Review Comment

github_reply_to_review_comment

Reply to an existing PR review comment, continuing the thread rather than starting a new one. Specify repo, PR number, comment ID, and reply body.

Instructions

Replies on an existing review thread rather than starting a new one.

Workflow and conventions: github_get_skill('pr-review').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
bodyYes
pr_numberYes
repo_nameYes
comment_idYesThe review comment being replied to, which sets the thread
repo_ownerYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
idYes
bodyYes
lineNo
pathNo
sideNo
authorYes
html_urlYes
created_atYes
start_lineNo
start_sideNo
in_reply_to_idNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv42.0.0

TDQS

A3.9/5.0
Behavior3/5

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

Annotations already indicate readOnlyHint=false (mutation), so the description's 'replies' aligns. It adds the nuance that it operates on an existing thread, which is not explicit in the schema. However, it lacks details on authentication requirements or response behavior, but given the annotations, a baseline of 3 is appropriate.

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?

The description is short (two sentences) and front-loads the core behavior: 'Replies on an existing review thread rather than starting a new one.' The reference to the workflow is extra but useful. No filler or redundancy.

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 mutation tool with an output schema, the description covers the main differentiation (reply vs new thread) and points to a skill for broader context. It does not detail all parameters or effects beyond the schema, but given the output schema and annotations, it is adequate for an agent to select and invoke correctly in most cases.

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?

The schema has only 20% description coverage, with only comment_id described as 'the review comment being replied to, which sets the thread.' The description does not elaborate on the other parameters like body or repo_name, but these are relatively self-explanatory. Given low coverage, the description could have done more, but the essential purpose of comment_id is covered in the schema. Baseline 3 is defensible.

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 states a specific action (reply on an existing review thread) and explicitly contrasts it with starting a new one, which distinguishes it from sibling tools like github_add_inline_pr_comment and github_submit_review. It also references the workflow convention via github_get_skill('pr-review').

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 makes clear that this tool is for replying to an existing thread, implying when not to use it (when starting a new thread). However, it does not explicitly name alternative tools for the opposite case or provide conditions like 'if you need to start a new thread, use X'. Despite that, the context is strong.

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