tomevault-io Design Tournament
A two-phase "wisdom of crowds" pattern for design work. Multiple independent agents explore the same problem in isolation, then independent rankers evaluate and merge the findings into a confidence-weighted stack ranking.
When to Use
- Designing a new feature, data structure, algorithm, or API
- Exploring multiple valid architectural approaches
- Story/task breakdown where the "right" decomposition isn't obvious
- Any design decision where independent perspectives reduce blind spots
Invocation
/design-tournament <problem statement>
The <problem statement> is the full description of what needs to be designed.
If no argument is given, ask the user for the problem statement before
proceeding.
Phase 1 — Diverge (Parallel Exploration)
Launch 5 independent agents in parallel using the Task tool with
subagent_type=general-purpose. Every agent receives identical instructions
so that their outputs are independently generated with zero cross-contamination.
All 5 agents MUST be launched in a single message (one message, five Task tool calls) so they run concurrently.
Agent Prompt Template (identical for all 5)
Each agent receives this prompt, with {PROBLEM} replaced by the user's
problem statement and {AGENT_ID} set to a unique label (Alpha, Beta, Gamma,
Delta, Epsilon):
You are Design Agent {AGENT_ID} in an independent design tournament.
## Problem
{PROBLEM}
## Your Task
Produce a COMPLETE, standalone design proposal. You are working independently —
do not assume anyone else's output exists.
### Required Sections
1. **Problem Restatement** — Restate the problem in your own words to confirm
understanding. Call out any ambiguities or assumptions you are making.
2. **Design Proposal** — Your recommended design. Include:
- Core idea / approach (1-2 sentence summary)
- Detailed description with concrete types, signatures, or pseudocode
- Key invariants or contracts the design enforces
- How the design handles edge cases and failure modes
3. **Alternatives Considered** — At least 2 alternative approaches you
evaluated and why you rejected them.
4. **Trade-offs** — Explicit trade-off analysis:
- What does this design optimize for?
- What does it sacrifice?
- Under what conditions would a different design be better?
5. **Risks & Open Questions** — What could go wrong? What remains uncertain?
6. **Self-Assessment** — Rate your own confidence (0-100) in this design and
explain why.
### Rules
- Be specific and concrete — pseudocode or type signatures over hand-waving.
- Do NOT hedge with "it depends" — commit to a design and defend it.
- Explore the codebase if you need context (use Glob, Grep, Read).
- Aim for depth over breadth. One well-defended design beats three sketches.
### Output Format
Return your response as a single markdown document with the sections above.
Start with: `# Design Proposal — Agent {AGENT_ID}`
Collecting Results
After all 5 agents complete, gather their outputs. If any agent fails or times out, proceed with the agents that succeeded (minimum 3 required).
Phase 2 — Converge (Parallel Ranking)
Launch 2 independent ranking agents in parallel using the Task tool with
subagent_type=general-purpose. Both receive identical instructions and
the collected Phase 1 outputs.
Both rankers MUST be launched in a single message (one message, two Task tool calls) so they run concurrently.
Ranker Prompt Template (identical for both)
You are Ranking Judge {JUDGE_ID} in a design tournament.
## Original Problem
{PROBLEM}
## Design Proposals
Below are {N} independently generated design proposals for the same problem.
Evaluate them WITHOUT knowing which agent produced each one (they are labeled
Alpha through Epsilon for reference only).
{PROPOSALS}
## Your Task
### 1. Evaluation Criteria
Score each proposal on these dimensions (1-10 scale):
| Criterion | Weight | Description |
|-----------|--------|-------------|
| **Correctness** | 25% | Does the design actually solve the problem? Are invariants sound? |
| **Simplicity** | 20% | Is this the simplest design that could work? Minimal moving parts? |
| **Robustness** | 20% | How well does it handle edge cases, failures, and adversarial inputs? |
| **Extensibility** | 15% | Can the design accommodate likely future requirements without rework? |
| **Specificity** | 10% | How concrete and implementable is the proposal? |
| **Trade-off Awareness** | 10% | Does the author understand what they're sacrificing? |
### 2. Per-Proposal Evaluation
For EACH proposal, provide:
- Scores on each criterion
- Weighted total score
- Top strength (1 sentence)
- Top weakness (1 sentence)
- Key insight unique to this proposal (if any)
### 3. Stack Ranking
Produce a final ranking from best to worst. For each position:
- Rank position (1 = best)
- Agent label
- Weighted total score
- Confidence in this ranking position (0-100):
- 90-100: Clear winner/loser, large score gap
- 70-89: Solid ranking, meaningful score gap
- 50-69: Close call, could reasonably swap with adjacent rank
- Below 50: Essentially tied, ranking is arbitrary
### 4. Synthesis Recommendation
After ranking, provide:
- **Recommended design**: Which proposal to use as the starting point
- **Cherry-pick list**: Specific ideas from OTHER proposals that should be
incorporated into the winner
- **Composite confidence** (0-100): Your overall confidence that the #1
ranked proposal (with cherry-picks) is the right design
### Rules
- Judge designs on MERIT, not on writing quality or verbosity.
- If two designs are substantively identical, say so — don't force a
false distinction.
- Be willing to rank a simple, correct design above an elaborate one.
- Explore the codebase if you need context to evaluate feasibility.
### Output Format
Return your response as a single markdown document.
Start with: `# Ranking Report — Judge {JUDGE_ID}`
Merging Rankings
After both rankers complete, merge their results:
- For each proposal, average the weighted scores from both judges.
- For each rank position, compute:
- Average score
- Agreement: did both judges assign the same rank? (yes/no)
- Combined confidence: average of both judges' per-position confidence, reduced by 15 points if they disagree on rank position
- Final stack ranking by averaged weighted score (descending).
- Synthesize cherry-pick lists from both judges into a unified list.
Final Output Format
Present the merged result to the user as:
## Design Tournament Results
### Problem
{one-line restatement}
### Stack Ranking
| Rank | Agent | Avg Score | Judge Agreement | Confidence | Key Strength |
|------|-------|-----------|-----------------|------------|--------------|
| 1 | ... | 8.2/10 | Yes | 92% | ... |
| 2 | ... | 7.5/10 | Yes | 78% | ... |
| 3 | ... | 6.8/10 | No (J1:#2,J2:#4)| 54% | ... |
| ... | ... | ... | ... | ... | ... |
### Recommended Design
**Base**: Agent {winner}'s proposal
**Cherry-picks from other proposals**:
- From Agent X: {specific idea}
- From Agent Y: {specific idea}
**Composite Confidence**: {average of both judges' composite}%
### Winning Proposal Summary
{2-3 paragraph summary of the #1 design with cherry-picks integrated}
### Full Proposals (collapsed)
<details><summary>Agent Alpha — Score: X.X</summary>
{full proposal text}
</details>
{repeat for each agent}
### Ranking Details (collapsed)
<details><summary>Judge 1 Report</summary>
{full ranking report}
</details>
<details><summary>Judge 2 Report</summary>
{full ranking report}
</details>
Configuration
The default is 5 explorers + 2 rankers (7 total agents). If the user specifies
a different count (e.g., /design-tournament 3 agents: ...), respect it but
enforce these minimums:
- Phase 1: at least 3 explorer agents
- Phase 2: always exactly 2 ranking agents
Tips
- For large or ambiguous problems, include relevant file paths or context in the problem statement so explorer agents can read the codebase.
- If the problem involves existing code, tell agents which files to examine.
- The skill works for any design task: features, data structures, algorithms, API shapes, system architecture, task decomposition, migration plans.
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