Coordinate three agents in an adversarial debate to produce a binding consensus document.
npx skills add https://github.com/rshade/agent-skills --skill decide-rshade
Please help me install this Agent Skill. Skill: decide Source: https://github.com/rshade/agent-skills/tree/main/skills/decide Command: npx skills add https://github.com/rshade/agent-skills --skill decide-rshade
Coordinates a structured three-agent adversarial debate to surface divergent viewpoints and synthesize a binding consensus for strategic decisions. By forcing explicit positions, external research, and risk analysis, it reduces epistemic bias and uncertainty in high-stakes choices.
Run a three-agent debate to surface risks and synthesize a binding consensus for a strategic decision.
High-intent search queries and answers about installing and using this skill.
Adversarial debate for strategic decision-making works by running three parallel agents: two advocates developing competing positions and one moderator providing critical appraisal. This structured workflow forces explicit positions, external research, and risk analysis to synthesize a binding consensus that reduces epistemic bias in high-stakes choices.
A three-agent consensus protocol coordinates an Advocate A, Advocate B, and Moderator to conduct phase-driven adversarial debate. Each advocate cites at least two external sources while the moderator challenges with counter-evidence, ultimately yielding a binding consensus document with defined risks, mitigations, timeline, and metrics.
Yes, this structured debate workflow is explicitly designed for make-vs-buy decisions, product strategy pivots, and policy framing in uncertain environments. The adversarial consensus mechanism surfaces divergent viewpoints and tradeoffs, making it applicable when choosing among alternatives or evaluating high-stakes strategic options.
Running a parallel sub-agent debate requires each advocate agent to cite at least two external sources while developing their competing position. The moderator agent challenges both advocates with counter-evidence across a phase-driven workflow, ensuring all claims are grounded in research before synthesizing the final consensus.
Evaluating tradeoffs in high-stakes choices is best handled through an adversarial consensus approach that forces explicit competing positions and counter-arguments. By requiring external research citations and a moderator's critical appraisal, the process surfaces risks and mitigations that a single-perspective analysis would miss.
An adversarial consensus workflow should not be used for low-stakes or time-critical decisions, as it enforces a rigorous phase-driven debate requiring parallel sub-agents and external research. It is built specifically for high-stakes strategic choices where surfacing divergent viewpoints and reducing epistemic bias justifies the overhead.
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