llm-judge
Use when comparing two or more code implementations against a spec or requirements doc. Triggers on \"which repo is better\", \"compare these implementations\", \"evaluate both solutions\", \"rank these codebases\", or \"judge which approach wins\". Also covers choosing between competing PRs or vendor submissions solving the same problem. Does NOT review a single codebase for quality \u2014 use code review skills instead. Does NOT evaluate strategy docs \u2014 use strategy-review. Requires a spec file and 2+ repo paths.
npx skills add majiayu000/claude-skill-registry --skill llm-judge --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# LLM Judge Compare code implementations across multiple repositories using structured evaluation. ## Usage ```bash /beagle-analysis:llm-judge <spec> <repo1> <repo2> [repo3...] [--labels=...] [--weights=...] [--branch=...] ``` ## Arguments | Argument | Required | Description | |----------|----------|-------------| | `spec` | Yes | Path to spec/requirements document | | `repos` | Yes | 2+ paths to repositories to compare | | `--labels` | No | Comma-separated labels (default: directory names) | | `--weights` | No | Override weights, e.g. `functionality:40,security:30` | | `--branch` | No | Branch to compare against main (default: `main`) | ## Workflow 1. Parse `$ARGUMENTS` into `spec_path`, `repo_paths`, `labels`, `weights`, and `branch`. 2. Validate the spec file, each repo path, and the minimum repo count. 3. Read the spec document into memory. 4. Load this skill and the supporting reference files. 5. Spawn one Phase 1 repo agent per repository to gather facts only. 6. Validate the repo-agent JSON results before proceeding. 7. Spawn one Phase 2 judge agent per dimension. 8. Aggregate scores, compute weighted totals, rank repos, and write the report. 9. Display the markdown summary
- Usage
- Arguments
- Workflow
- Hard gates
- Command Workflow
- Step 1: Parse Arguments
- Step 2: Validate Inputs
- Step 3: Read Spec Document
- Step 4: Load the Skill
- Step 5: Phase 1 - Spawn Repo Agents
- Step 6: Validate Phase 1 Results
- Step 7: Phase 2 - Spawn Judge Agents
- Step 8: Aggregate Scores
- Step 9: Generate Verdict
for repo in "${REPO_PATHS[@]}"; do
done
echo "$FACTS" | python3 -c "import json,sys; json.load(sys.stdin)" 2>/dev/null || { echo "Error: Invalid JSON from $LABEL"; exit 1; }
mkdir -p .beagle
python3 -c "import json; json.load(open('.beagle/llm-judge-report.json'))" && echo "Valid report"What does the llm-judge skill do?
Use when comparing two or more code implementations against a spec or requirements doc. Triggers on \"which repo is better\", \"compare these implementations\", \"evaluate both solutions\", \"rank these codebases\", or \"judge which approach wins\". Also covers choosing between competing PRs or vendor submissions solving the same problem. Does NOT review a single codebase for quality \u2014 use code review skills instead. Does NOT evaluate strategy docs \u2014 use strategy-review. Requires a spec file and 2+ repo paths.
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill llm-judge --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.