Key benefits:
Works with
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionsadd:judge-with-debateExecute the skills CLI command in your project's root directory to begin installation:
Fetches sadd:judge-with-debate from neolabhq/context-engineering-kit and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate sadd:judge-with-debate. Access via /sadd:judge-with-debate in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
0
total installs
0
this week
765
GitHub stars
0
upvotes
Run in your terminal
0
installs
0
this week
765
stars
Key benefits:
This command implements iterative multi-judge debate:
Phase 0: Setup
mkdir -p .specs/reports
|
Phase 0.5: Dispatch Meta-Judge
Meta-Judge (Opus)
|
Evaluation Specification YAML
|
Phase 1: Independent Analysis (3 judges in parallel)
+- Judge 1 -> {name}.1.md -+
Solution +- Judge 2 -> {name}.2.md -+-+
+- Judge 3 -> {name}.3.md -+ |
|
Phase 2: Debate Round (iterative) |
Each judge reads others' reports |
| |
Argue + Defend + Challenge |
(grounded in eval specification) |
| |
Revise if convinced --------------+
| |
Check consensus |
+- Yes -> Final Report |
+- No -> Next Round ---------+
Before starting evaluation, ensure the reports directory exists:
mkdir -p .specs/reports
Report naming convention: .specs/reports/{solution-name}-{YYYY-MM-DD}.[1|2|3].md
Where:
{solution-name} - Derived from solution filename (e.g., users-api from src/api/users.ts){YYYY-MM-DD} - Current date[1|2|3] - Judge numberBefore independent analysis, dispatch a meta-judge agent to generate a tailored evaluation specification. The meta-judge runs ONCE and produces rubrics, checklists, and scoring criteria that ALL judges will use across ALL rounds.
Meta-judge prompt template:
## Task
Generate an evaluation specification yaml for the following evaluation task. You will produce rubrics, checklists, and scoring criteria that multiple judge agents will use to evaluate the solution through independent analysis and multi-round debate.
CLAUDE_PLUGIN_ROOT=`${CLAUDE_PLUGIN_ROOT}`
## User Prompt
{task description - what the solution was supposed to accomplish}
## Context
{Any relevant context about the solution being evaluated}
## Artifact Type
{code | documentation | configuration | etc.}
## Evaluation Mode
Multi-judge debate with consensus-seeking across rounds
## Instructions
Return only the final evaluation specification YAML in your response.
The specification should support both independent analysis and debate-based refinement.
Dispatch:
Use Task tool:
- description: "Meta-judge: generate evaluation specification for {solution-name}"
- prompt: {meta-judge prompt}
- model: opus
- subagent_type: "sadd:meta-judge"
Wait for the meta-judge to complete and extract the evaluation specification YAML from its output before proceeding to Phase 1.
Launch 3 independent judge agents in parallel (Opus for rigor):
.specs/reports/{solution-name}-{date}.[1|2|3].mdKey principle: Independence in initial analysis prevents groupthink.
Prompt template for initial judges:
You are Judge {N} evaluating a solution independently against an evaluation specification produced by the meta judge.
CLAUDE_PLUGIN_ROOT=`${CLAUDE_PLUGIN_ROOT}`
## Solution
{path to solution file(s)}
## Task Description
{what the solution was supposed to accomplish}
## Evaluation Specification
```yaml
{meta-judge's evaluation specification YAML}
.specs/reports/{solution-name}-{date}.{N}.md
Follow your full judge process as defined in your agent instructions!
Additional instructions:
Add to report beginning Done by Judge {N}
**Dispatch each judge:**
Use Task tool:
### Phase 2: Debate Rounds (Iterative)
For each debate round (max 3 rounds):
Launch **3 debate agents in parallel**:
1. Each judge agent receives:
- Path to their own previous report (`.specs/reports/{solution-name}-{date}.[1|2|3].md`)
- Paths to other judges' reports (`.specs/reports/{solution-name}-{date}.[1|2|3].md`)
- The original solution
- The meta-judge's evaluation specification YAML
2. Each judge:
- Identifies disagreements with other judges (>1 point score gap on any criterion)
- Defends their own ratings with evidence from the solution and evaluation specification
- Challenges other judges' ratings they disagree with
- Considers counter-arguments
- Revises their assessment if convinced
3. Updates their report file with new section: `## Debate Round {R}`
4. After they reply, if they reached agreement move to Phase 3: Consensus Report
**Key principle:** Judges communicate only through filesystem - orchestrator doesn't mediate and don't read reports files itself, it can overflow your context.
**Prompt template for debate judges:**
```markdown
You are Judge {N} in debate round {R}.
CLAUDE_PLUGIN_ROOT=`${CLAUDE_PLUGIN_ROOT}`
## Your Previous Report
{path to .specs/reports/{solution-name}-{date}.{N}.md}
## Other Judges' Reports
Judge 1: .specs/reports/{solution-name}-{date}.1.md
...
## Task Description
{what the solution was supposed to accomplish}
## Solution
{path to solution}
## Evaluation Specification
```yaml
{meta-judge's evaluation specification YAML}
.specs/reports/{solution-name}-{date}.{N}.md (append to existing file)
Follow your full judge process as defined in your agent instructions!
Additional debate instructions:
CRITICAL:
**Dispatch each debate judge:**
Use Task tool:
### Consensus Check
After each debate round, check for consensus:
**Consensus achieved if:**
- All judges' overall scores within 0.5 points of each other
- No criterion has >1 point disagreement across any two judges
- All judges explicitly state they accept the consensus
**If no consensus after 3 rounds:**
- Report persistent disagreements
- Provide all judge reports for human review
- Flag that automated evaluation couldn't reach consensus
**Orchestration Instructions:**
**Step 1: Dispatch Meta-Judge (Phase 0.5)**
1. Launch meta-judge agent
2. Wait for meta-judge to complete
3. Extract the evaluation specification YAML from meta-judge output
**Step 2: Run Independent Analysis (Phase 1)**
1. Launch 3 judge agents in parallel (Judge 1, 2, 3) with the evaluation specification YAML
2. Each writes their independent assessment to `.specs/reports/{solution-name}-{date}.[1|2|3].md`
3. Wait for all 3 agents to complete
**Step 3: Check for Consensus**
Let's work through this systematically to ensure accurate consensus detection.
Read all three reports and extract:
- Each judge's overall weighted score
- Each judge's score for every criterion
Check consensus step by step:
1. First, extract all overall scores from each report and list them explicitly
2. Calculate the difference between the highest and lowest overall scores
- If difference <= 0.5 points -> overall consensus achieved
- If difference > 0.5 points -> no consensus yet
3. Next, for each criterion, list all three judges' scores side by side
4. For each criterion, calculate the difference between highest and lowest scores
- If any criterion has difference > 1.0 point -> no consensus on that criterion
5. Finally, verify consensus is achieved only if BOTH conditions are met:
- Overall scores within 0.5 points
- All criterion scores within 1.0 point
**Step 4: Decision Point**
- **If consensus achieved**: Go to Step 6 (Generate Consensus Report)
- **If no consensus AND round < 3**: Go to Step 5 (Run Debate Round)
- **If no consensus AND round = 3**: Go to Step 7 (Report No Consensus)
**Step 5: Run Debate Round**
1. Increment round counter (round = round + 1)
2. Launch 3 judge agents in parallel with the same evaluation specification YAML
3. Each agent reads:
- Their own previous report from filesystem
- Other judges' reports from filesystem
- Original solution
4. Each agent appends "Debate Round {R}" section to their own report file
5. Wait for all 3 agents to complete
6. Go back to Step 3 (Check for Consensus)
**Step 6: Reply with Report**
Let's synthesize the evaluation results step by step.
1. Read all final reports carefully
2. Before generating the report, analyze the following:
- What is the consensus status (achieved or not)?
- What were the key points of agreement across all judges?
- What were the main areas of disagreement, if any?
- How did the debate rounds change the evaluations?
3. Reply to user with a report that contains:
- If there is consensus:
- Consensus scores (average of all judges)
- Consensus strengths/weaknesses
- Number of rounds to reach consensus
- Final recommendation with clear justification
- If there is no consensus:
- All judges' final scores showing disagreements
- Specific criteria where consensus wasn't reached
- Analysis of why consensus couldn't be reached
- Flag for human review
4. Command complete
**Step 7: Report No Consensus**
- Report persistent disagreements
- Provide all judge reports for human review
- Flag that automated evaluation couldn't reach consensus
### Phase 3: Consensus Report
If consensus achieved, synthesize the final report by working through each section methodically:
```markdown
# Consensus Evaluation Report
Let's compile the final consensus by analyzing each component systematically.
## Consensus Scores
First, let's consolidate all judges' final scores:
| Criterion | Judge 1 | Judge 2 | Judge 3 | Final |
|-----------|---------|---------|---------|-------|
| {Name} | {X}/5 | {X}/5 | {X}/5 | {X}/5 |
...
**Consensus Overall Score**: {avg}/5.0
## Consensus Strengths
[Review each judge's identified strengths and extract the common themes that all judges agreed upon]
## Consensus Weaknesses
[Review each judge's identified weaknesses and extract the common themes that all judges agreed upon]
## Debate Summary
Let's trace how consensus was reached:
- Rounds to consensus: {N}
- Initial disagreements: {list with specific criteria and score gaps}
- How resolved: {for each disagreement, explain what evidence or argument led to resolution}
## Final Recommendation
Based on the consensus scores and the key strengths/weaknesses identified:
{Pass/Fail/Needs Revision with clear justification tied to the evidence}
.specs/reports/ (created if not exists).specs/reports/{solution-name}-{date}.1.md, .specs/reports/{solution-name}-{date}.2.md, .specs/reports/{solution-name}-{date}.3.mdMake data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
sadd:judge-with-debate reduced setup friction for our internal harness; good balance of opinion and flexibility.
sadd:judge-with-debate has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: sadd:judge-with-debate is focused, and the summary matches what you get after install.
sadd:judge-with-debate is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Registry listing for sadd:judge-with-debate matched our evaluation — installs cleanly and behaves as described in the markdown.
sadd:judge-with-debate fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
Useful defaults in sadd:judge-with-debate — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Solid pick for teams standardizing on skills: sadd:judge-with-debate is focused, and the summary matches what you get after install.
We added sadd:judge-with-debate from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Useful defaults in sadd:judge-with-debate — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
showing 1-10 of 53