Imported from oimiragieo/agent-studio (.claude/skills/adversarial-debate/SKILL.md). Install upstream with npx skills add oimiragieo/agent-studio --skill adversarial-debate. Copyright stays with the author.

Adversarial Debate

Overview

Runs a structured N-round debate between two opposing agents (pro and con) on any decision-requiring topic, then synthesizes a moderator recommendation. Built for architectural decisions, technology choices, security trade-offs, and design reviews — anywhere strong opinions exist and the right answer is non-obvious.

When to Use

• Architecture decision records (ADRs) needing structured justification
• Technology selection (e.g., Redis vs Postgres, REST vs GraphQL)
• Security trade-off analysis (e.g., strict vs permissive auth policy)
• Design review of competing approaches
• Any HIGH/EPIC task where the planner identifies genuine disagreement among specialists

Do not use for:

• Settled best practices (where there is consensus)
• Simple implementation tasks
• Decisions already made and documented in ADRs

Iron Law

NO RECOMMENDATION WITHOUT CITED DEBATE EVIDENCE

The moderator's synthesis MUST reference specific arguments made during rounds. A recommendation that ignores debate content is invalid.

Debate Protocol

Pre-Debate: Stance Assignment

Before any rounds begin, the invoking agent MUST define:

1. Topic — one clear decision question (not open-ended)
2. Pro stance — what the PRO agent advocates for
3. Con stance — what the CON agent argues against / alternative
4. Number of rounds — default 3, max 5
5. Success criteria — what a good recommendation looks like

Example:

Topic: Should we use event sourcing for the order service?
Pro stance: Yes — event sourcing provides audit trail and temporal queries
Con stance: No — event sourcing adds complexity; CRUD with snapshots is sufficient
Rounds: 3

Round Structure

Each round follows this fixed sequence:

Step 1: PRO Argument

PRO agent argues its stance with:
- 1 primary argument (specific, concrete)
- 1 supporting piece of evidence (metric, case study, or first-principles reasoning)
- 1 anticipated objection pre-addressed

Step 2: CON Rebuttal

CON agent responds with:
- Direct refutation of PRO's primary argument (must engage it — no deflection)
- 1 counter-argument from CON's stance
- 1 counter-evidence or challenge to PRO's evidence

Step 3: Round Score

Score each round immediately using this rubric (0–10 per dimension):

Round Score = mean(Specificity, Evidence, Rebuttal Quality, Relevance)

Track cumulative scores per agent across rounds.

Final Synthesis (Moderator)

After all rounds, the moderator agent produces a structured synthesis:

## Debate Summary

**Topic:** [restate topic]
**Rounds completed:** N
**PRO total score:** X.X/10
**CON total score:** X.X/10

## Key Arguments

**Strongest PRO argument:** [cite round + argument]
**Strongest CON argument:** [cite round + argument]

## Decision Factors

List 3-5 factors that should determine which stance wins in context:

1. Factor: [e.g., team expertise] → Favors: [PRO/CON/neutral]
2. ...

## Recommendation

**Decision:** [clear recommendation — not "it depends"]
**Confidence:** [High / Medium / Low]
**Rationale:** [2-3 sentences citing specific debate evidence from rounds]

## Conditions / Caveats

[Any conditions under which the recommendation should be revisited]

Workflow

Step 0: Load Context and Memory

# Check for prior debate results on same topic
grep -r "adversarial-debate" C:/dev/projects/agent-studio/.claude/context/memory/decisions.md 2>/dev/null | tail -5

Check .claude/context/memory/decisions.md for prior ADRs on same topic. If a prior debate exists, acknowledge it and note whether conditions have changed.

Step 1: Parse and Validate Input

Validate input against schemas/input.schema.json:

node .claude/skills/adversarial-debate/hooks/pre-execute.cjs '{"topic":"...","proStance":"...","conStance":"...","rounds":3}'

Expected output: { "valid": true } or error listing missing fields.

Step 2: Run Debate Rounds

For each round 1..N:

1. PRO agent produces its argument (following Round Structure above)
2. CON agent produces rebuttal (must reference PRO's specific argument)
3. Score the round using the rubric — output a score table
4. Record round to scripts/main.cjs output buffer

Step 3: Moderator Synthesis

After all rounds, produce the Final Synthesis following the template in templates/implementation-template.md.

The moderator MUST:

• Reference at least 2 specific round arguments by round number
• State a single clear recommendation (not "it depends without conditions")
• Assign a confidence level (High/Medium/Low) with justification

Step 4: Persist Decision

Append result to .claude/context/memory/decisions.md:

echo "## [$(date +%Y-%m-%d)] Adversarial Debate: {TOPIC}
- Recommendation: {DECISION}
- Confidence: {CONFIDENCE}
- Rounds: {N}
- Cite: {KEY_EVIDENCE_SUMMARY}" >> .claude/context/memory/decisions.md

Step 5: Emit Observability Event

const { sendEvent } = require('.claude/tools/observability/send-event.cjs');
sendEvent({
  tool_name: 'adversarial-debate',
  agent_id: process.env.AGENT_ID || 'unknown',
  session_id: process.env.SESSION_ID || 'unknown',
  outcome: 'success',
});

Enforcement Hooks

Input validated against schemas/input.schema.json before execution. Output contract defined in schemas/output.schema.json.

Pre-execution hook: hooks/pre-execute.cjs — validates topic, stances, rounds range (1-5). Post-execution hook: hooks/post-execute.cjs — emits observability event via send-event.cjs.

Anti-Patterns

• Never let agents pick their own stances — stance drift produces muddled debates
• Never skip round scoring — unscored debates allow moderator bias in synthesis
• Never produce "it depends" recommendations without explicit conditions listed
• Never use more than 5 rounds — beyond round 3, new arguments rarely emerge
• Never invoke debate for trivial decisions — overhead not justified for settled questions

Related Skills

• llm-council — parallel multi-LLM synthesis (complementary: debate is sequential, council is parallel)
• advanced-elicitation — meta-cognitive reasoning for single-agent analysis
• plan-generator — use debate output as an ADR input to plan-generator
• sequential-thinking — structured problem decomposition for the topic before debate

Memory Protocol

Before starting: Read .claude/context/memory/decisions.md for prior ADRs on related topics.

After completing: Append structured summary to .claude/context/memory/decisions.md with date, topic, recommendation, confidence, and key evidence citations.

Do not write directly to patterns.json, gotchas.json, or open-findings.json — use MemoryRecord tool.