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team-reviewer

Aggregate parallel specialized reviewers to analyze pull request and local diff changes.

1|2|Updated Apr 6, 2026
Search Tags:#automation#security#scoring#code-review#pull-request#test-coverage#diff-analysis
One-click install
npx skills add https://github.com/parisgroup-ai/imersao-ia-setup --skill team-reviewer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: team-reviewer
Source: https://github.com/parisgroup-ai/imersao-ia-setup/tree/main/skills/team-reviewer
Command: npx skills add https://github.com/parisgroup-ai/imersao-ia-setup --skill team-reviewer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Large or complex pull requests and local diffs are hard to review thoroughly by a single reviewer; this Skill orchestrates multiple specialized reviewer agents in parallel, consolidates their findings, and produces a prioritized, scored report to speed decision-making and reduce missed issues.

Core Features & Use Cases

  • Scatter-gather review: Spawn specialized agents (security, code-quality, type-design, test-coverage, commit-hygiene, silent-failure) to run in parallel against a PR or local diff.
  • Automated aggregation and scoring: Parse agent outputs, normalize severity-tagged findings, compute weighted dimension scores, and produce a final verdict (CLEAN, NEEDS_ATTENTION, SIGNIFICANT_ISSUES, BLOCK).
  • Integrations & fallbacks: Uses the gh CLI to fetch PR diffs or falls back to local git diffs, handles agent timeouts and unparseable outputs with conservative defaults.
  • Use case: Run a quick security-and-quality pass on a large feature branch before merge to surface critical issues and quantify overall readiness.

Quick Start

Ask the assistant to run the team-reviewer skill against the current branch or a specific PR number to produce a scored review report.

Frequently Asked Questions about team-reviewer

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

FAQPage Schema
How do I run parallel code reviews on a pull request to check security and test coverage?▼

Parallel pull request code reviews are orchestrated by spawning specialized agents for security, code-quality, test-coverage, and commit-hygiene assessments simultaneously against a PR diff, producing a consolidated scored report with severity-tagged findings.

Can I use automated PR review scoring on local git diffs without a GitHub pull request?▼

Yes, automated PR review scoring works on local git diffs as a fallback. The system uses the gh CLI to fetch PR diffs when available, but automatically falls back to local git diffs to generate the same scored severity-tagged report.

What is a scatter-gather code review and how does it handle large feature branches?▼

Scatter-gather code review is a mechanism that spawns multiple specialized reviewer agents in parallel to analyze large feature branches, aggregating their outputs to compute weighted dimension scores and a final readiness verdict.

Do I need the gh CLI installed to analyze pull request diffs for code-quality and type-design issues?▼

Yes, you need the gh CLI installed and authenticated to fetch pull request diffs directly. If gh CLI access is unavailable, the review falls back to parsing local git diffs to perform the same code-quality and type-design assessments.

How does automated code review handle agent timeouts and unparseable outputs during diff analysis?▼

Automated diff analysis handles agent timeouts and unparseable outputs by applying conservative defaults. This ensures the final verdict and severity-tagged findings remain reliable even when specialized review agents fail to return structured results.

What's the best way to quantify overall code readiness before merging a complex pull request?▼

The best way to quantify code readiness is to aggregate parallel specialized reviewer outputs into weighted dimension scores. This produces a final verdict ranging from CLEAN to BLOCK, prioritizing critical security and quality issues for merge decision-making.

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