Spawns parallel Claude subagents to query AI providers, evaluate response quality with follow-ups, and deliver structured insights including confidence ratings and blind spot analysis for complex architectural decisions or --agents flag.
From claude-councilnpx claudepluginhub hex/claude-marketplace --plugin claude-councilThis skill uses the workspace's default tool permissions.
agent-prompt-template.mdSearches, retrieves, and installs Agent Skills from prompts.chat registry using MCP tools like search_skills and get_skill. Activates for finding skills, browsing catalogs, or extending Claude.
Searches prompts.chat for AI prompt templates by keyword or category, retrieves by ID with variable handling, and improves prompts via AI. Use for discovering or enhancing prompts.
Guides agent creation for Claude Code plugins with file templates, frontmatter specs (name, description, model), triggering examples, system prompts, and best practices.
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.
For each provider, display the agent's structured analysis 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