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sentry-pr-code-review

Parse and verify Seer by Sentry bug prediction comments in GitHub pull requests.

Updated Jun 4, 2026
Search Tags:#automation#code review#github#sentry#seer#bug prediction
One-click install
npx skills add https://github.com/achmf/KostaHub --skill sentry-pr-code-review-achmf
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: sentry-pr-code-review
Source: https://github.com/achmf/KostaHub/tree/main/.agents/skills/sentry-pr-code-review
Command: npx skills add https://github.com/achmf/KostaHub --skill sentry-pr-code-review-achmf

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires gh, jq.

What problem does it solve?

This Skill addresses the manual overhead of reviewing and resolving bug predictions generated by Seer by Sentry, ensuring that AI-identified code issues are addressed efficiently during the pull request process.

Core Features & Use Cases

  • Automated Parsing: Automatically extracts bug descriptions, severity levels, and suggested fixes from Seer bot comments.
  • Workflow Integration: Streamlines the verification of code issues by mapping bot feedback to specific file lines and providing a structured reporting format.
  • Use Case: When a developer opens a pull request, use this Skill to scan for all unresolved Seer comments, verify the validity of the findings against the current codebase, and generate a summary report of resolved versus skipped issues.

Quick Start

Invoke the sentry-pr-code-review skill to analyze all pending Seer bug predictions for the current pull request.

Frequently Asked Questions about sentry-pr-code-review

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate Seer bug prediction reviews in GitHub pull requests?▼

Automate Seer bug prediction reviews by scanning GitHub pull requests to identify, parse, and verify unresolved Seer bot comments against the current file states. This generates a structured summary report of resolved versus skipped code issues to streamline code quality workflows.

Can I use GitHub CLI to parse Sentry Seer bot comments?▼

Yes, you can use GitHub CLI to query pull request comments and metadata for Sentry Seer bot comments. The skill cross-references bot-generated feedback with current file states to determine actionable fixes.

What is the best way to verify AI-identified code issues from Sentry Seer?▼

The best way to verify AI-identified code issues from Sentry Seer is to cross-reference bot-generated feedback with current file states. This determines actionable fixes by mapping bug descriptions, severity levels, and suggested fixes to specific file lines.

Do I need jq installed to automate Sentry code review workflows?▼

Yes, you need jq installed along with the GitHub CLI to automate Sentry code review workflows. These dependencies are required to query pull request metadata and parse bot comments for unresolved bug predictions.

How does automated Seer comment parsing handle severity levels and suggested fixes?▼

Automated Seer comment parsing extracts bug descriptions, severity levels, and suggested fixes directly from bot comments. It maps this feedback to specific file lines and cross-references the current codebase to verify the validity of the findings.

What are the limitations of automating Sentry Seer bug prediction reviews?▼

Limitations of automating Sentry Seer bug prediction reviews include requiring appropriate repository permissions and specific dependencies like GitHub CLI and jq. The process only resolves issues that can be cross-referenced with current file states within the pull request.

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