council▌
boshu2/agentops · updated May 6, 2026
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Parallel multi-model consensus review with configurable perspectives, debate rounds, and deep exploration.
- ›Supports three task modes: validate (PASS/WARN/FAIL verdicts), brainstorm (explore alternatives), and research (deep analysis with trade-offs)
- ›Spawns 2–3 independent judges by default; scales to 6+ agents with --deep , --mixed (Claude + Codex), and --explorers sub-agents, capped at 12 total
- ›Debate mode ( --debate ) runs two-round adversarial review with verdict exchange and posi
/council — Multi-Model Consensus Council
Spawn parallel judges with different perspectives, consolidate into consensus. Works for any task — validation, research, brainstorming.
Quick Start
/council --quick validate recent # fast inline check
/council validate this plan # validation (2 agents)
/council brainstorm caching approaches # brainstorm
/council validate the implementation # validation (critique triggers map here)
/council research kubernetes upgrade strategies # research
/council research the CI/CD pipeline bottlenecks # research (analyze triggers map here)
/council --preset=security-audit validate the auth system # preset personas
/council --deep --explorers=3 research upgrade automation # deep + explorers
/council --debate validate the auth system # adversarial 2-round review
/council --deep --debate validate the migration plan # thorough + debate
/council # infers from context
Council works independently — no RPI workflow, no ratchet chain, no ao CLI required. Zero setup beyond initial install.
Modes
| Mode | Agents | Execution Backend | Use Case |
|---|---|---|---|
--quick |
0 (inline) | Self | Fast single-agent check, no spawning |
| default | 2 | Runtime-native (Codex sub-agents preferred; Claude teams fallback) | Independent judges (no perspective labels) |
--deep |
3 | Runtime-native | Thorough review |
--mixed |
3+3 | Runtime-native + Codex CLI | Cross-vendor consensus |
--debate |
2+ | Runtime-native | Adversarial refinement (2 rounds) |
/council --quick validate recent # inline single-agent check, no spawning
/council recent # 2 runtime-native judges
/council --deep recent # 3 runtime-native judges
/council --mixed recent # runtime-native + Codex CLI
Spawn Backend (MANDATORY)
Council requires a runtime that can spawn parallel subagents and (for --debate) send messages between agents. Use whatever multi-agent primitives your runtime provides. If no multi-agent capability is detected, fall back to --quick (inline single-agent).
Required capabilities:
- Spawn subagent — create a parallel agent with a prompt (required for all modes except
--quick) - Agent messaging — send a message to a specific agent (required for
--debate)
Skills describe WHAT to do, not WHICH tool to call. See skills/shared/SKILL.md for the capability contract.
After detecting your backend, read the matching reference for concrete spawn/wait/message/cleanup examples:
- Shared Claude feature contract →
skills/shared/references/claude-code-latest-features.md - Local mirrored contract for runtime-local reads →
references/claude-code-latest-features.md - Claude Native Teams →
references/backend-claude-teams.md - Codex Sub-Agents / CLI →
references/backend-codex-subagents.md - Background Tasks →
references/backend-background-tasks.md - Inline (
--quick) →references/backend-inline.md
See also references/cli-spawning.md for council-specific spawning flow (phases, timeouts, output collection).
When to Use --debate
Use --debate for high-stakes or ambiguous reviews where judges are likely to disagree:
- Security audits, architecture decisions, migration plans
- Reviews where multiple valid perspectives exist
- Cases where a missed finding has real consequences
Skip --debate for routine validation where consensus is expected. Debate adds R2 latency (judges stay alive and process a second round via backend messaging).
Incompatibilities:
--quickand--debatecannot be combined.--quickruns inline with no spawning;--debaterequires multi-agent rounds. If both are passed, exit with error: "Error: --quick and --debate are incompatible."--debateis only supported with validate mode. Brainstorm and research do not produce PASS/WARN/FAIL verdicts. If combined, exit with error: "Error: --debate is only supported with validate mode."
Task Types
| Type | Trigger Words | Perspective Focus |
|---|---|---|
| validate | validate, check, review, assess, critique, feedback, improve | Is this correct? What's wrong? What could be better? |
| brainstorm | brainstorm, explore, options, approaches | What are the alternatives? Pros/cons? |
| research | research, investigate, deep dive, explore deeply, analyze, examine, evaluate, compare | What can we discover? What are the properties, trade-offs, and structure? |
Natural language works — the skill infers task type from your prompt.
First-pass rigor gate for plan/spec validation (MANDATORY)
When mode is validate and the target is a plan/spec/contract (or contains boundary rules, state transitions, or conformance tables), judges must apply this gate before returning PASS:
- Canonical mutation + ack sequence is explicit, single-path, and non-contradictory.
- Consume-at-most-once path is crash-safe with explicit atomic boundary and restart recovery semantics.
- Status/precedence behavior is defined with a field-level truth table and anomaly reason codes for conflicting evidence.
- Conformance includes explicit boundary failpoint tests and deterministic assertions for replay/no-duplicate-effect outcomes.
Verdict policy for this gate:
- Missing or contradictory gate item: minimum
WARN. - Missing deterministic conformance coverage for any gate item: minimum
WARN. - Critical lifecycle invariant not mechanically verifiable:
FAIL.
Architecture
Context Budget Rule (CRITICAL)
Judges write ALL analysis to output files. Messages to the lead contain ONLY a
minimal completion signal: {"type":"verdict","verdict":"...","confidence":"...","file":"..."}.
The lead reads output files during consolidation. This prevents N judges from
exploding the lead's context window with N full reports via SendMessage.
Consolidation runs inline as the lead — no separate chairman agent. The lead reads each judge's output file sequentially with the Read tool and synthesizes.
Execution Flow
┌─────────────────────────────────────────────────────────────────┐
│ Phase 1: Build Packet (JSON) │
│ - Task type (validate/brainstorm/research) │
│ - Target description │
│ - Context (files, diffs, prior decisions) │
│ - Perspectives to assign │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ Phase 1a: Select spawn backend │
│ codex_subagents | claude_teams | background_fallback │
│ Team lead = spawner (this agent) │
└─────────────────────────────────────────────────────────────────┘
│
┌─────────────────┴─────────────────┐
▼ ▼
┌───────────────────────┐ ┌───────────────────────┐
│ RUNTIME-NATIVE JUDGES│ │ CODEX AGENTS │
│ (spawn_agent or teams)│ │ (Bash tool, parallel)│
│ │ │ Agent 1 (independent │
│ Agent 1 (independent │ │ or with preset) │
│ or with preset) │ │ Agent 2 │
│ Agent 2 │ │ Agent 3 │
│ Agent 3 (--deep only)│ │ (--mixed only) │
│ (--deep/--mixed only)│ │ │
│ │ │ Output: JSON + MD │
│ Write files, then │ │ Files: .agents/ │
│ wait()/SendMessage to │ │ council/codex-* │
│ lead │ │ │
│ Files: .agents/ │ └───────────────────────┘
│ council/claude-* │ │
└───────────────────────┘ │
│ │
└─────────────────┬─────────────────┘
▼
┌─────────────────────────────────────────────────────────────────┐
│ Phase 2: Consolidation (Team Lead — inline, no extra agent) │
│ - Receive MINIMAL completion signals (verdict + file path) │
│ - Read each judge's output file with Read tool │
│ - If schema_version is missing from a judge's output, treat │
│ as version 0 (backward compatibility) │
│ - Compute consensus verdict │
│ - Identify shared findings │
│ - Surface disagreements with attribution │
│ - Generate Markdown report for human │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ Phase 3: Cleanup │
│ - Cleanup backend resources (close_agent / TeamDelete / none) │
└─────────────────────────────────────────────────────────────────┘
│
▼
┌─────────────────────────────────────────────────────────────────┐
│ Output: Markdown Council Report │
│ - Consensus: PASS/WARN/FAIL │
│ - Shared findings │
│ - Disagreements (if any) │
│ - Recommendations │
└─────────────────────────────────────────────────────────────────┘
Step 1b: Load Project Reviewer Config
Check for project-level reviewer configuration before spawning judges:
REVIEWER_CONFIG=".agents/reviewer-config.md"
if [ -f "$REVIEWER_CONFIG" ]; then
# Parse YAML frontmatter for reviewer list
# Example .agents/reviewer-config.md:
# ---
# reviewers:
# - security-sentinel
# - architecture-strategist
# - code-simplicity-reviewer
# plan_reviewers:
# - architecture-strategist
# skip_reviewers:
# - performance-oracle
# ---
# Additional review context goes in the markdown body.
fi
If reviewer-config.md exists:
- Use
reviewerslist to select which judge perspectives to spawn - Use
plan_reviewersfor plan validation specifically - Use
skip_reviewersto exclude perspectives even if preset includes them - Pass markdown body as additional context to all judges
If no config exists, use defaults (current behavior unchanged).
For schema details and an example, see references/reviewer-config-example.md.
Graceful Degradation
| Failure | Behavior |
|---|---|
| 1 of N agents times out | Proceed with N-1, note in report |
| All Codex CLI agents fail | Proceed with runtime-native judges only, note degradation |
| All agents fail | Return error, suggest retry |
| Codex CLI not installed | Skip Codex CLI judges, continue with runtime judges only (warn user) |
| No multi-agent capability | Fall back to --quick (inline single-agent review) |
| No agent messaging | --debate unavailable, single-round review only |
| Output dir missing | Create .agents/council/ automatically |
Timeout: 120s per agent (configurable via --timeout=N in seconds).
Minimum quorum: At least 1 agent must respond for a valid council. If 0 agents respond, return error.
Effort Levels for Judges
Use the effort command to optimize token spend per judge role:
| Agent Role | Recommended Effort | Rationale |
|---|---|---|
| Judges (validate/research) | low |
Judges review evidence, not implement — shallow reasoning suffices |
| Explorers | low |
Fast breadth-first scanning |
| Chairman (consolidation) | medium |
Needs balanced reasoning for consensus synthesis |
Pre-Flight Checks
- Multi-agent capability: Detect whether runtime supports spawning parallel subagents. If not, degrade to
--quick. - Agent messaging: Detect whether runtime supports agent-to-agent messaging. If not, disable
--debate. - Codex CLI judges (--mixed only): Check
which codex, test model availability, test--output-schemasupport. Downgrade mixed mode when unavailable. - Agent count: Verify
judges * (1 + explorers) <= MAX_AGENTS (12) - Output dir:
mkdir -p .agents/council
Quick Mode (--quick)
Single-agent inline validation. No subprocess spawning, no Task tool, no Codex. The current agent performs a structured self-review using the same output schema as a full council.
When to use: Routine checks, mid-implementation sanity checks, pre-commit quick scan.
Execution: Gather context (files, diffs) -> perform structured self-review inline using the council output_schema (verdict, confidence, findings, recommendation) -> write report to .agents/council/YYYY-MM-DD-quick-<target>.md labeled as Mode: quick (single-agent).
Limitations: No cross-perspective disagreement, no cross-vendor insights, lower confidence ceiling. Not suitable for security audits or architecture decisions.
Packet Format (JSON)
The packet sent to each agent. File contents are included inline — agents receive the actual code/plan text in the packet, not just paths. This ensures both Claude and Codex agents can analyze without needing file access.
If .agents/ao/environment.json exists, include it in the context packet so judges can reason about available tools and environment state.
Judge prompt boundary:
- Do NOT include
.agents/references in judge prompts. - Do NOT instruct judges to search
.agents/directories. Judges operate on the council packet only.
{
"council_packet": {
"version": "1.0",
"mode": "validate | brainstorm | research",
"target": "Implementation of user authentication system",
"context": {
"files": [
{
"path": "src/auth/jwt.py",
"content": "<file contents inlined here>"
},
{
"path": "src/auth/middleware.py",
"content": "<file contents inlined here>"
}
]How to use council on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add council
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches council from GitHub repository boshu2/agentops and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate council. Access the skill through slash commands (e.g., /council) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.8★★★★★59 reviews- ★★★★★Shikha Mishra· Dec 28, 2024
council has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Hana Wang· Dec 16, 2024
Useful defaults in council — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Arjun Robinson· Dec 16, 2024
council has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Isabella Bhatia· Dec 8, 2024
I recommend council for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Lucas Robinson· Dec 8, 2024
council is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Ganesh Mohane· Dec 4, 2024
council is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Hana Li· Nov 27, 2024
Keeps context tight: council is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yash Thakker· Nov 19, 2024
Solid pick for teams standardizing on skills: council is focused, and the summary matches what you get after install.
- ★★★★★Isabella Chawla· Nov 7, 2024
We added council from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Arjun Iyer· Nov 7, 2024
Solid pick for teams standardizing on skills: council is focused, and the summary matches what you get after install.
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