stochastic-multi-agent-consensus
Spawn N agents (default 5), each given a distinct role/mental-model lens (Conservative Expert, First-Principles Thinker, Disruptive Contrarian, Pragmatic…
Skill by sairithik9849
Chalk Labs
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Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/sairithik9849-stochastic-multi-agent-consensus
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: agent-building
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/stochastic-multi-agent-consensus
Tools it pre-approves 6
From allowed-tools in SKILL.md: the agent may use these without asking you each time.
Read,Grep,Glob,Bash,Agent,Write
What's inside
- Skill name
stochastic-multi-agent-consensus- Description
- Spawn N agents (default 5), each given a distinct role/mental-model lens (Conservative Expert, First-Principles Thinker, Disruptive Contrarian, Pragmatic Operator, Systems Thinker), to independently scan the search space for a question and surface a spectrum of solutions from low-hanging fruit to high-variance outliers. The orchestrator clusters the results and aggregates to the statistical mode (frequency-weighted consensus) in a single pass — no debate, no rounds. Use for decision-making, ranking options, strategic analysis, or any problem where you want a wide, high-variance discovery scan. Triggers on "consensus", "stochastic consensus", "poll agents", "spawn N agents to analyze", "discover solutions", "scan the search space", "multi-agent vote", "what do N agents think", "get multiple opinions", or "/stochastic-multi-agent-consensus". Produces a debate-ready artifact of structured positions. NOT for simple factual lookups, single-answer questions, or code edits — those don't need a panel. For an identical-prompt fan-out merged into a single terminal answer (with a cross-model researcher), use fan-out-fan-in instead. For stateful multi-round debate where agents challenge and revise each other's positions, use the model-chat refine skill on this skill's output artifact — that debate loop lives there, not here.
- License
- unknown
- Allowed tools
- Read,, Grep,, Glob,, Bash,, Agent,, Write
- Instructions
- 181 lines in SKILL.md · view on GitHub
Before installing
- Pre-approves some shell commands
Agent Skills spec issues
- description: longer than 1024 characters
Files (1)
- SKILL.md
The license isn't open source, so the instructions aren't shown here. Read SKILL.md on GitHub
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Signals
- Stars
- 0
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Jul 29, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- License unknown
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
More from sairithik9849
- 0.519score
fan-out-fan-in
sairithik9849
Answer a divergent, open-ended question (no single right answer — strategy, design trade-offs, "what are the best approaches to X", comparisons, ideation) by…
SkillBFreshness: BClaude Code +9 - 0.511score
model-chat
sairithik9849
Spawn 3+ Claude Code instances (default 3, up to 5+) into a shared debate room where they challenge, disagree, and converge across multiple rounds.
SkillBFreshness: BClaude Code +9 - 0.494score
codebase-design
sairithik9849
Shared vocabulary for designing deep modules.
SkillBFreshness: BClaude Code +9 - 0.491score
improve-codebase-architecture
sairithik9849
Scan a codebase for deepening opportunities, present them as a visual HTML report, then grill through whichever one you pick.
SkillBFreshness: BClaude Code +9 - 0.489score
grill-me
sairithik9849
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree.
SkillBFreshness: BClaude Code +9
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Cite this page
stochastic-multi-agent-consensus skill. Agent Mart. https://agentmart.dev/skills/sairithik9849-stochastic-multi-agent-consensus (last updated 2026-10-24)