From claude-council
Spawns parallel Claude subagents to query providers, evaluate response quality, and return structured insights with confidence ratings and blind spot analysis. For complex architectural decisions or with --agents flag.
How this skill is triggered — by the user, by Claude, or both
Slash command
/claude-council:deep-executionThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Use parallel Claude subagents for deeper analysis. Each subagent queries its provider,
Use parallel Claude subagents for deeper analysis. Each subagent queries its provider, evaluates response quality, can ask follow-up questions, and returns structured insights.
For each selected provider, gather:
${CLAUDE_PLUGIN_ROOT}/scripts/providers/{name}.shbash ${CLAUDE_PLUGIN_ROOT}/scripts/query-council.sh --list-available or read the provider script defaultsLaunch ALL provider agents in a single message (multiple Agent tool calls) for parallel execution.
Use run_in_background: true and subagent_type: "general-purpose" for each.
Agent prompt template: See agent-prompt-template.md for the full template.
Read it and fill in {PROVIDER}, {SCRIPT_PATH}, and {QUESTION} for each agent.
CRITICAL: If a role was assigned to a provider (via --roles), prepend the role context to the question before passing it to the agent. Use the same role injection format as the standard flow.
CRITICAL: If file context was gathered (via --file or auto-context), include it in the question passed to each agent.
As each background agent completes, you will be automatically notified. Wait for ALL agents to complete before proceeding to display.
If an agent fails or times out, note the failure and continue with available results.
Validate each agent's reply against the contract before using it:
echo "$AGENT_REPLY_JSON" | bash ${CLAUDE_PLUGIN_ROOT}/scripts/validate-analysis.sh
[invalid agent analysis - raw reply preserved], list the validator's
reasons, and exclude that provider from confidence-weighted synthesis
(mention it under Divergence/failures instead).For each provider with a valid analysis, display it using this format:
## {EMOJI} {PROVIDER} ({MODEL}) — Agent Analysis
**Quality**: {quality} | **Confidence**: {confidence} | **Retried**: {retried}
### Key Recommendations
{recommendations}
### Unique Perspective
{unique_perspective}
### Blind Spots
{blind_spots}
---
<details>
<summary>Full {PROVIDER} Response</summary>
{full_response}
</details>
Provider emojis (ALWAYS use emoji + space):
With pre-analyzed responses, generate a richer synthesis than the standard mode:
Weight agreement by each provider's confidence level. High-confidence agreement is stronger signal than low-confidence agreement.
Cross-reference each provider's blind spots against other providers' recommendations. Flag risks that NO provider considered.
Where providers disagree, explain WHY they likely diverge (different assumptions, different optimization targets, different risk tolerance).
Synthesize the strongest approach, noting which providers support it and at what confidence level.
Save the complete output (all provider analyses + synthesis) to a cache file:
mkdir -p .claude/council-cache
Write the output to .claude/council-cache/council-agents-{TIMESTAMP}.md where
TIMESTAMP is the current Unix timestamp.
Tell the user:
Full agent analysis saved to
.claude/council-cache/council-agents-{TIMESTAMP}.md
npx claudepluginhub hex/claude-marketplace --plugin claude-councilExecutes council queries by running the query pipeline across selected AI providers (Gemini, OpenAI, Grok, Perplexity), displays formatted responses verbatim, and generates a synthesis of consensus, divergence, and recommendations.
Runs a configurable multi-LLM council with personas, budget caps, synthesis, veto gates, and optional implementation handoff via the orchestrate.sh runner.
Orchestrates three-phase LLM consensus protocol coordinating Claude, OpenAI Codex, and Google Gemini CLIs for collaborative code review, multi-model problem-solving, and decision-making.