Roundtable Adaptive

Adaptive multi-model AI roundtable. Runs up to 4 AI models (configurable) in 2 debate rounds with cross-critique and formal consensus scoring. Requires a configured Anthropic provider (Claude Opus recommended). Optionally adds GPT-5.3 Codex (OpenAI), Grok 4, and Gemini 3.1 Pro via Blockrun proxy. Works with Claude-only fallback if optional providers are unavailable. Writes results to local filesystem. Debate panel agents are persistent thread sessions; meta-panel and synthesis agents are one-shot.

Roundtable v2 — Adaptive Multi-Model Orchestrator

Trigger: roundtable [--mode] [prompt] from any channel your agent monitors. Output: Posted to your configured output channel (set ROUNDTABLE_OUTPUT_CHANNEL in your OpenClaw config, or results are posted back to the triggering channel). Panel agents: Persistent sessions (mode="session", thread=true) — stay alive in the Discord thread for follow-up questions. Meta-panel analysts and synthesis agent are one-shot (mode="run").

The orchestrator = COORDINATOR ONLY. Uses your default model unless overridden in panels.json. Never argues a position, never joins the panel.

Core principle: the Meta-Panel (4 premium models) designs the optimal WORKFLOW for the task — parallel debate, sequential pipeline, or hybrid — then the right agents execute it.

Configuration

Before using, set your output channel in panels.json (or the triggering channel is used):

json

{
  "output": {
    "channel": "discord",
    "target": "YOUR_CHANNEL_ID_HERE"
  }
}

If using Discord threads (optional — creates one thread per roundtable for clean organization):

json

{
  "output": {
    "channel": "discord",
    "target": "YOUR_CHANNEL_ID_HERE",
    "useThreads": true
  }
}

Without this config, results are posted directly to the channel where the command was issued.

Cost transparency

Component	Cost per full run
Claude Opus (OAuth)	Free
GPT-5.3 Codex (OAuth)	Free
Gemini 3.1 Pro (Blockrun)	~$0.05
Grok 4 (Blockrun)	~$0.08
Total (full panel)	~$0.13–$0.50
Degraded mode (Claude only)	Free

--quick flag halves cost (1 round only).

---

Setup

Minimum (degraded mode — free):

1. Configure anthropic provider in openclaw.json (OAuth or API key)
2. Optionally add openai-codex for GPT-5.3 Codex
3. Done — Grok/Gemini slots fall back to Claude Sonnet

Full panel (adds Grok 4 + Gemini 3.1 Pro via Blockrun):

1. Install Blockrun: openclaw plugins install @blockrun/clawrouter then openclaw gateway restart
2. Fund the Blockrun wallet with USDC on Base (~$5-10). Address shown during install.
3. Full panel costs ~$0.13–$0.50/run; Claude and GPT slots remain free via OAuth.

Results are saved to {workspace}/memory/roundtables/YYYY-MM-DD-slug.json (created automatically).

---

Trigger Patterns

Optional: auto-trigger a dedicated channel

You can configure a Discord channel as a roundtable-only channel in your AGENTS.md:

text

Any message in channel [YOUR_CHANNEL_ID] → treat as a roundtable topic automatically.
No prefix needed. Message → auto-detect mode → create thread → spawn orchestrator.

This is entirely optional — the explicit roundtable command works from any channel.

Explicit trigger (any channel)

Explicit trigger (any channel)

• roundtable [prompt] — auto-detect mode, full flow
• roundtable --debate [prompt] — force parallel debate mode
• roundtable --build [prompt] — force build/coding mode
• roundtable --redteam [prompt] — force adversarial mode
• roundtable --vote [prompt] — force decision mode
• roundtable --quick [prompt] — skip meta-panel, use default panel for mode, 1 round only
• roundtable --panel model1,model2,model3 [prompt] — manual panel override, skip meta-panel
• roundtable --validate [prompt] — add Round 3 agent validation of synthesis
• roundtable --no-search [prompt] — skip web search (use only for purely theoretical/abstract topics)

---

Step -1: Create a Thread (FIRST ACTION)

Before anything else, create a thread in your configured channel and save the thread ID.

-1a) Dedup check (REQUIRED)

Avoid double-spawn if the same topic is triggered twice.

1. Normalize topic string:
   • lowercase
   • trim
   • collapse multiple spaces
   • remove trailing punctuation
2. List recent threads in the target channel:

text

message(action='thread-list', channel='discord', channelId='[CHANNEL_ID]', limit=25)

3. If an existing active thread title matches normalized topic (+ same mode tag like [[DEBATE]]) created in last 24h:
   • reuse that thread (THREAD_ID = existing_thread_id)
   • post: ♻️ Duplicate topic detected — reusing existing thread.
   • do NOT spawn a new orchestrator/panel
4. If no match: create a new thread.

-1b) Create thread (if no dedup hit)

text

message(
  action = 'thread-create',
  channel = '[your configured channel]',
  channelId = '[CHANNEL_ID from user config]',
  threadName = '🎯 [topic — max 8 words] [[MODE]]',
  message = '**Panel:** [model list]\n**Mode:** [mode] | **Rounds:** [N]\n⏳ Analysis in progress...'
)

Save the returned thread ID as THREAD_ID.

All subsequent message() calls use target = THREAD_ID, NOT the channel ID.

If thread creation fails or channel is not configured: fall back to posting directly in the active channel.

---

Step 0: Web Search Grounding (always first)

Run a web search on the topic before anything else — meta-panel and all agents will have current context.

text

web_search(query = prompt, count = 5)

Timeout policy: If web_search returns no result or errors within ~10s, do NOT block — continue immediately with CURRENT_CONTEXT = "No real-time data available (search failed or timed out).". The roundtable proceeds on model knowledge only.

Caching: If re-running the same topic within the same session, reuse the prior CURRENT_CONTEXT block — do not re-search.

Summarize results into a CURRENT_CONTEXT block (max 250 words):

• Key facts, recent developments, relevant data points
• Date of search
• If no useful results found: note "No relevant real-time data found" and continue

This block is injected into:

1. The meta-panel prompt (so they design the workflow with current context)
2. Every Round 1 agent prompt (so all panelists argue from the same updated baseline)

---

Step 0b: Meta-Panel — Workflow Design

Skip if: --panel flag used, OR --quick flag used.

Spawn 4 premium meta-analysts in parallel

Read panels.json → meta.models. For each:

text

sessions_spawn(
  task = filled prompts/meta-panel.md,
  model = model_id,
  mode = "run",
  label = "rt-meta-[A/B/C/D]",
  runTimeoutSeconds = 90
)

0b. Synthesize workflow from 4 recommendations

After collecting all meta responses, the orchestrator synthesizes the final workflow:

1. Workflow type: majority vote among 4 recommendations

   • Tie → prefer hybrid (more flexible)

2. Stage composition: tally model recommendations per stage

   • For each stage position, pick the most-recommended model
   • If a model is not in agents.defaults.models allowlist → skip, use next
   • If a model is your orchestrator's model → skip (reserved for the orchestrator, never a panelist)

3. Rounds: median of recommendations (round up if tie) — hard cap at 3 max, always

4. Synthesis model: most-recommended premium model not on the main panel

5. Log the decision (include in output header):

   "Meta-panel designed workflow: [type]. Stages: [N]. Panel: [models]. Synthesis: [model]."

0c. Workflow types explained

parallel_debate — classic roundtable

• All agents in Stage 1 work independently, same prompt
• Round 2: cross-critique
• Best for: debates, opinions, risk analysis, decision-making

sequential — output chains between stages

• Stage 1 agents produce outputs (drafts, code, research)
• Stage 2 agents receive Stage 1 outputs and review/validate/improve
• Best for: coding (write → review), research (collect → synthesize), creative (draft → refine)
• Round 2 within Stage 1 still possible; Stage 2 is a separate pass

hybrid — parallel within stages, sequential between

• Stage 1: N agents work in parallel on different aspects
• Stage 2: 1-2 premium agents receive ALL Stage 1 outputs and produce integrated output
• Best for: complex analysis (parallel research → premium synthesis)

0d. Panel degradation rule

If any agent fails and fallback is SAME MODEL FAMILY → log: ⚠️ PANEL DEGRADED — [role] substituted [original] with [fallback] (same family: [family])

Always surface this in META section of final output with actionable guidance:

• If degraded due to missing blockrun → "Action: Start Blockrun at localhost:8402 for full panel, or use --panel budget for stable 2-model run"
• If degraded due to model not in allowlist → "Action: Add [model] to agents.defaults.models in openclaw.json"
• If degraded due to API error → "Action: Check provider API key / quota, then retry"

---

Step 1: Detect Mode (if no flag given)

Mode	Keywords
debate	pros/cons, tradeoff, should we, ethics, compare, opinion, better
build	implement, code, architecture, build, design, develop, create
redteam	attack, vulnerability, failure, risk, break, threat, exploit
vote	choose, decide, which one, best option, select, recommend between
default	anything else

---

Step 2: Execute Workflow

parallel_debate (standard)

Round 1: Spawn all panel agents in parallel as persistent thread-bound sessions.

text

sessions_spawn(
  task = filled prompts/round1.md,
  model = model_id,
  mode = "session",        ← persistent — stays alive in the thread
  label = "rt-[role]",
  thread = true            ← bound to the thread from Step -1
)

• Save session keys: { "attacker": sessionKey, "defender": sessionKey, ... }
• Each agent writes their full response + SELF-DIGEST (last section)
• Collect all self-digests
• ⚠️ Agents stay alive — users can address them directly for follow-up questions

Round 2 (if rounds ≥ 2): Send cross-critique prompt to each existing session via sessions_send.

• Do NOT re-spawn — reuse session keys from Round 1
• [SELF_DIGEST] = this agent's own digest from Round 1
• [PEER_DIGESTS] = other agents' digests (labeled with role)
• Extract AGREEMENT SCORES from each response

Round 3 (if --validate): See Step 4.

sequential

Stage 1: Spawn agents in parallel as persistent sessions (mode="session", thread=true).

• Use standard prompts/round1.md.
• Round 2 cross-critique via sessions_send to existing sessions (no re-spawn).
• Collect full Stage 1 outputs for Stage 2.

Stage 2: Spawn new persistent sessions (mode="session", thread=true).

• Build prompt: prompts/round1.md base + prepend Stage 1 outputs as context
• Label: "STAGE 1 OUTPUT from [Role]: [full output]"
• Stage 2 agents review/validate/improve Stage 1 work and write SELF-DIGESTs

hybrid

Stage 1: Parallel persistent sessions (mode="session", thread=true), each with a different sub-task.

• Customize Round 1 prompt to specify each agent's sub-task:

  "Your specific task for this stage: [task from workflow design]"

• Agents write SELF-DIGESTs

Stage 2: 1-2 new persistent sessions (mode="session", thread=true) with all Stage 1 outputs embedded.

• Build prompt: prompts/round1.md base + "You are integrating and synthesizing the work of multiple agents. Their outputs: [all Stage 1 outputs]"
• Stage 2 produces the integrated output

---

Step 3: Consensus Scoring

After Round 2 (parallel_debate) or Stage 2 (sequential/hybrid):

Extract AGREEMENT SCORES from each agent's Round 2 response. Build score matrix: { agent_role: { peer_role: score_1_to_5 } } Consensus % = (sum of all scores / (n_scores × 5)) × 100 If no Round 2 scores (quick mode / sequential): omit consensus %, mark as "N/A"

Note on Round 3: Round 3 validation uses ACCURATE/PARTIALLY/INACCURATE — this is a separate metric from consensus %. Round 3 checks synthesis fidelity, not inter-agent agreement. Do NOT mix these two metrics. Consensus % comes only from Round 2 scores; Round 3 result appears separately in the META block as Validated: yes/no/partial.

---

Step 4: Round 3 — Validation (--validate flag only)

When to recommend --validate to the user:

• Consensus % < 40% (high disagreement — synthesis risks distortion)
• Redteam mode (adversarial stakes — synthesis must be bulletproof)
• Build mode with 3+ Stage 2 models (complex integration, easy to misrepresent)
• User explicitly mentions "high-stakes", "final decision", or "publishing this"

When NOT to use it: Quick mode, debate on subjective topics, or when time matters more than precision.

Draft synthesis first (Step 5 below), but do NOT post.

Spawn validation agents:

text

sessions_spawn(
  task = filled prompts/round3-validation.md,
  model = original agent model,
  label = "rt-r3-validate-[role]",
  runTimeoutSeconds = 60
)

Tally:

• 2+ INACCURATE → rewrite synthesis incorporating corrections
• 1 INACCURATE → note in META: ⚠️ [Role] flagged misrepresentation: [correction summary]
• All ACCURATE/PARTIAL → mark Validated: yes or Validated: partial in META

---

Step 5: Synthesis — Spawned Neutral Model

Never write synthesis yourself.

text

sessions_spawn(
  task = filled prompts/final-synthesis.md,
  model = [synthesis model from meta-panel recommendation, or anthropic/claude-opus-4-6 as default],
  label = "rt-synthesis",
  mode = "run",
  runTimeoutSeconds = 180
)

Fill prompts/final-synthesis.md placeholders:

• [ROUND1_SUMMARIES] → all self-digests: "[ROLE] ([model]): [digest]"
• [ROUND2_SUMMARIES] → critiques: "[ROLE] criticized [peer]'s [claim] because [reason]"
• [CONSENSUS_SCORES] → full score matrix + calculated %
• [DISCORD_THREAD_ID] → the THREAD_ID from Step -1 (synthesis agent posts here)

Post to Discord using THREAD_ID from Step -1 (not the channel ID). All round outputs and the final synthesis go into the same thread.

---

Step 6: Persist Results

Save to {workspace}/memory/roundtables/YYYY-MM-DD-[topic-slug].json:

json

{
  "date": "YYYY-MM-DD",
  "topic": "[prompt]",
  "mode": "[mode]",
  "workflow_type": "parallel_debate|sequential|hybrid",
  "stages": [{ "model": "...", "role": "...", "task": "..." }],
  "meta_panel_recommendation": "[summary of meta votes]",
  "panel_degraded": false,
  "panel_degradation_notes": "",
  "consensus_pct": "XX% or N/A",
  "synthesis_model": "[model]",
  "validated": "yes|no|partial",
  "elapsed_time_sec": 0,
  "synthesis": "[final synthesis text]"
}

Also append one JSONL line to {workspace}/memory/roundtables/scorecard.jsonl with: ts, topic, mode, workflow_type, elapsed_time_sec, consensus_pct, validated, panel_degraded.

---

Edge Cases

Situation	Action
Web search fails	Continue with note "No real-time context available" in all prompts
--no-search flag	Skip Step 0 web search entirely
Meta-panel all fail	Use default panel for detected mode, log warning
--quick	Skip meta-panel + round 2. Always uses parallel_debate workflow. Spawns default panel for detected mode (3 models). Synthesizes after round 1 only.
--panel override	Skip meta-panel, use specified models, default to parallel_debate
Fallback = same family	Continue + log PANEL DEGRADED warning in META
Both model and fallback fail	Skip agent, note in META — do not wait, do not block
No blockrun configured	Warn user: "Blockrun not available. Using budget panel. Full panel requires Blockrun at localhost:8402." Auto-switch to budget profile from panels.json.
Agent timeout (any round)	FAIL-CONTINUE: treat as absent, mark [TIMEOUT] in META, proceed with surviving agents
Agent fails mid-Round 2	Use its Round 1 digest as final position, omit its scores from consensus calculation
Synthesis agent fails	Orchestrator writes synthesis, note: "Synthesis by orchestrator (bias risk — no neutral model available)"
Stage 2 agent fails	Note in META, synthesize with Stage 1 only
0 agents respond	Report failure, suggest retry
1 agent responds	Skip Round 2 (no peers), synthesize from Round 1 only, mark consensus "N/A"
--context-from SLUG	Load {workspace}/memory/roundtables/[slug].json, extract synthesis field, prepend to CURRENT_CONTEXT as "PRIOR ROUNDTABLE CONTEXT: [synthesis]". If file not found: warn and continue without prior context.

Placeholder Contract

When filling prompt templates, apply this rule for every [PLACEHOLDER]:

Placeholder	If missing/failed	Action
[CURRENT_CONTEXT]	Web search failed	Insert: "No real-time context available."
[SELF_DIGEST]	Agent timed out R1	Skip agent entirely from R2
[PEER_DIGESTS]	All peers failed	Skip R2, go to synthesis directly
[ROUND1_SUMMARIES]	No R1 outputs	Abort with error: "0 agents responded"
[ROUND2_SUMMARIES]	Quick mode / no R2	Insert: "No cross-critique (quick mode or single round)"
[CONSENSUS_SCORES]	No scores extracted	Insert: "N/A — scores not available"
[SYNTHESIS_DRAFT]	Synthesis failed	Skip R3, note in META

Never leave a [PLACEHOLDER] unfilled in a prompt. Unfilled placeholders confuse models and produce garbage output.

Score Parsing (Round 2)

Agents write scores in free text. Extract scores with this heuristic:

1. Look for the SCORES: block
2. Match pattern: - [Role]: X/5 — extract integer X (1–5)
3. If no clean integer found, scan for digit 1–5 nearest to the role name
4. If still ambiguous → assign 3 (neutral) and note [SCORE INFERRED] in META Do NOT crash the workflow on a malformed score block.

---

Quick Reference: Default Panels (fallback if meta-panel fails)

json

debate:  [opus-4.6, gpt-5.3-codex, gemini-3.1-pro, grok-4] → Advocate / Devil's Advocate / Analyst / Contrarian
build:   [opus-4.6, gemini-3.1-pro, grok-4, gpt-5.3-codex] → Architect / Reviewer / Engineer / Implementer
redteam: [opus-4.6, gemini-3.1-pro, grok-4, gpt-5.3-codex] → Defender / Analyst / Attacker / Red Teamer
vote:    [opus-4.6, gemini-3.1-pro, grok-4, gpt-5.3-codex]  → 4-way vote panel
(all via blockrun/ prefix — see panels.json for exact model IDs and fallbacks)