nemoclaw-maintainer-pr-comparator

star 21.3k

Compares competing PRs that target the same issue and recommends which one to merge. Runs gate, correctness, and quality checks; outputs a deterministic scorecard with reasoning trace. Use when an issue has two or more open PRs and a maintainer needs to decide which to merge.

NVIDIA By NVIDIA schedule Updated 6/17/2026

name: nemoclaw-maintainer-pr-comparator description: Compares competing PRs that target the same issue and recommends which one to merge. Runs gate, correctness, and quality checks; outputs a deterministic scorecard with reasoning trace. Use when an issue has two or more open PRs and a maintainer needs to decide which to merge. user_invocable: true

PR Comparator

Picks the merge winner among competing PRs for a single issue. Tier 0 gates eliminate plumbing failures; Tiers 1-2 score correctness and quality; Tier 3 applies deterministic tiebreakers. Degraded mode handles the case where no PR passes gates.

Prerequisites

  • gh CLI installed and authenticated
  • A target repository with an issue that has 2+ open PRs

Repo policy

Defaults assume NemoClaw conventions (security CODEOWNERS, DCO, CodeRabbit, docs/ directory). For other repos, edit repo-policy.md to override.

Workflow

Copy this checklist into your response and check off each step:

PR Comparison Progress:
- [ ] Step 1: Parse issue (body + comments) for acceptance criteria
- [ ] Step 2: Discover candidate PRs (default-order search with stop conditions)
- [ ] Step 3: Detect supersession (parse PR bodies)
- [ ] Step 4: Run Tier 0 gates per PR
- [ ] Step 5: Run Tier 1 correctness checks per PR
- [ ] Step 6: Run Tier 2 quality checks per PR
- [ ] Step 7: Compute weighted scores
- [ ] Step 8: Apply Tier 3 ranking (happy path or degraded mode)
- [ ] Step 9: Emit verdict using templates/verdict.md

Step 1: Parse issue

Extract acceptance criteria from issue body and all comments:

gh issue view <issue-number> --json title,body,comments

Read every comment — commenters often add asks the body doesn't capture.

Step 2: Discover candidate PRs

scripts/find-candidates.sh <issue-number>

Applies a single default order with stop conditions.

Step 3: Detect supersession

scripts/parse-supersession.sh <pr-number-1> <pr-number-2> ...

Parses each PR body for supersedes #N, replaces #N, closes in favor of #N, folds in #N. A PR that supersedes another wins ties immediately.

Step 4: Tier 0 gates

scripts/collect-gates.sh <pr-number>
scripts/check-coderabbit-threads.sh <pr-number>

Five gates, all mandatory. See checks/tier-0-gates.md for the full list and interpretation.

Step 5: Tier 1 correctness

Six checks, all LLM judgments. See checks/tier-1-correctness.md for evidence requirements per check.

Step 6: Tier 2 quality

Three checks, all LLM judgments. See checks/tier-2-quality.md.

Step 7: Weighted score

  • Each pass = full points
  • Each yellow = half points
  • Each fail = zero
  • Tier 1 weight: 2.0× per check
  • Tier 2 weight: 1.0× per check

Step 8: Tier 3 ranking

Branch on whether any PR passes all Tier 0 gates. See tiebreakers.md for happy-path tiebreakers, degraded-mode distance-to-ready ranking, and the behavior-coverage matrix.

Step 9: Emit verdict

Use templates/verdict.md. Every judgment must carry evidence (file:line refs, diff snippets), reasoning chain, and the score it contributed.

Reference files

  • repo-policy.md — configurable defaults per target repo
  • checks/tier-0-gates.md — plumbing gates
  • checks/tier-1-correctness.md — six correctness checks
  • checks/tier-2-quality.md — three quality checks
  • tiebreakers.md — Tier 3 ranking and degraded mode
  • templates/verdict.md — output template
  • validation/backtest.md — backtest the skill against historical cases

Scripts (execute, do not read)

  • scripts/find-candidates.sh — PR discovery
  • scripts/collect-gates.sh — Tier 0 gate evaluation
  • scripts/check-coderabbit-threads.sh — GraphQL thread resolution
  • scripts/parse-supersession.sh — body parsing for supersession refs
  • scripts/render-verdict.py — verdict scorecard renderer

What this skill does NOT do

These require infrastructure beyond GitHub API + LLM and are deferred to v2 modules:

  • Running each PR's code against adversarial inputs (sandboxed execution)
  • Cross-issue regression sweep (separate skill)
  • Revert simulation against neighbor PRs
  • Static analyzer integration (CodeQL, Semgrep)
Install via CLI
npx skills add https://github.com/NVIDIA/NemoClaw --skill nemoclaw-maintainer-pr-comparator
Repository Details
star Stars 21,253
call_split Forks 2,832
navigation Branch main
article Path SKILL.md
More from Creator