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llm-council

@DNYoussef/context-cascade
10
0

Facilitate council-style deliberation among specialized models with structured prompts, evidence gates, and explicit confidence ceilings.

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name llm-council
description Facilitate council-style deliberation among specialized models with structured prompts, evidence gates, and explicit confidence ceilings.

LIBRARY-FIRST PROTOCOL (MANDATORY)

Before writing ANY code, you MUST check:

Step 1: Library Catalog

  • Location: .claude/library/catalog.json
  • If match >70%: REUSE or ADAPT

Step 2: Patterns Guide

  • Location: .claude/docs/inventories/LIBRARY-PATTERNS-GUIDE.md
  • If pattern exists: FOLLOW documented approach

Step 3: Existing Projects

  • Location: D:\Projects\*
  • If found: EXTRACT and adapt

Decision Matrix

Match Action
Library >90% REUSE directly
Library 70-90% ADAPT minimally
Pattern exists FOLLOW pattern
In project EXTRACT
No match BUILD (add to library after)

STANDARD OPERATING PROCEDURE

Purpose

Run council deliberations that collect diverse model opinions, enforce evidence-backed synthesis, and prevent overconfident consensus.

Trigger Conditions

  • Positive: multi-model debate, comparative reasoning, adjudication of conflicting outputs, need for weighted synthesis with evidence.
  • Negative: single-model answers, pure prompt polishing (route to prompt-architect), or skill creation (route to skill-forge).

Guardrails

  • Skill-Forge structure-first: maintain SKILL.md, examples/, tests/; add resources/ and references/ or log remediation tasks.
  • Prompt-Architect hygiene: define intent and constraints per council question; capture HARD/SOFT/INFERRED assumptions; output pure English with explicit ceilings.
  • Council safety: assign roles (proposer, challenger, judge), enforce registry agents, timebox rounds, and ensure hook latency budgets.
  • Adversarial validation: require dissenting review, cross-check citations, and COV on synthesis steps; capture evidence.
  • MCP tagging: store council transcripts with WHO=llm-council-{session} and WHY=skill-execution.

Execution Playbook

  1. Intent & scope: define the question, success metric, and constraints; confirm inferred items.
  2. Panel setup: select specialists, assign roles, and set scoring criteria; configure timeboxes.
  3. Deliberation rounds: gather proposals, run adversarial critiques, and request evidence per claim.
  4. Synthesis: weigh arguments, resolve conflicts, and produce a grounded recommendation with alternatives.
  5. Validation loop: check evidence integrity, run COV on synthesis, and record telemetry.
  6. Delivery: provide recommendation, rationale, dissent, risks, and confidence ceiling.

Output Format

  • Question, constraints, and panel composition.
  • Round summaries (proposals, critiques, evidence).
  • Synthesis with chosen path, alternatives, and risk notes.
  • Confidence: X.XX (ceiling: TYPE Y.YY) - rationale.

Validation Checklist

  • Structure-first assets present or planned; examples/tests updated or ticketed.
  • Roles/timeboxes enforced; evidence cited; registry-only agents used; hooks within budget.
  • Adversarial and COV results captured with MCP tags; confidence ceiling declared; English-only output.

Completion Definition

Council run is complete when a recommendation (or documented stalemate) is delivered with evidence, dissent captured, risks owned, and MCP log persisted.

Confidence: 0.70 (ceiling: inference 0.70) - Council orchestration rewritten with skill-forge scaffolding and prompt-architect constraint and confidence discipline.