consciousness-council
# consciousness-council This Claude Code skill runs a structured multi-perspective deliberation system that generates diverse viewpoints on complex questions by summoning 4–6 distinct cognitive archetypes, such as the Architect, Contrarian, Empiricist, Ethicist, Futurist, and Pragmatist, each with its own reasoning style and blind spots. Use it when facing decisions with no obvious answer, exploring problems from multiple angles, seeking devil's advocate analysis, or needing input from different expert perspectives simultaneously.
git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills /tmp/consciousness-council && cp -r /tmp/consciousness-council/skills/consciousness-council ~/.claude/skills/consciousness-councilSKILL.md
# Consciousness Council A structured multi-perspective deliberation system that generates genuine cognitive diversity on any question. Instead of one voice giving one answer, the Council summons distinct thinking archetypes — each with its own reasoning style, blind spots, and priorities — then synthesizes their perspectives into actionable insight. ## Why This Exists Single-perspective thinking has a ceiling. When you ask one mind for an answer, you get one frame. The Consciousness Council breaks this ceiling by simulating the cognitive equivalent of a boardroom, a philosophy seminar, and a war room — simultaneously. It's not roleplay. It's structured epistemic diversity. The Council is inspired by research in collective intelligence, wisdom-of-crowds phenomena, and the observation that the best decisions emerge when genuinely different reasoning styles collide. ## How It Works The Council has three phases: ### Phase 1 — Summon the Council Based on the user's question, select 4-6 Council Members from the archetypes below. Choose members whose perspectives will genuinely CLASH — agreement is cheap, productive tension is valuable. **The 12 Archetypes:** | # | Archetype | Thinking Style | Asks | Blind Spot | | --- | ------------------ | -------------------------------------- | -------------------------------------------- | ----------------------------------------- | | 1 | **The Architect** | Systems thinking, structure-first | "What's the underlying structure?" | Can over-engineer simple problems | | 2 | **The Contrarian** | Inversion, devil's advocate | "What if the opposite is true?" | Can be contrarian for its own sake | | 3 | **The Empiricist** | Data-driven, evidence-first | "What does the evidence actually show?" | Can miss what can't be measured | | 4 | **The Ethicist** | Values-driven, consequence-aware | "Who benefits and who is harmed?" | Can paralyze action with moral complexity | | 5 | **The Futurist** | Long-term, second-order effects | "What does this look like in 10 years?" | Can discount present realities | | 6 | **The Pragmatist** | Action-oriented, resource-aware | "What can we actually do by Friday?" | Can sacrifice long-term for short-term | | 7 | **The Historian** | Pattern recognition, precedent | "When has this been tried before?" | Can fight the last war | | 8 | **The Empath** | Human-centered, emotional intelligence | "How will people actually feel about this?" | Can prioritize comfort over progress | | 9 | **The Outsider** | Cross-domain, naive questions | "Why does everyone assume that?" | Can lack domain depth | | 10 | **The Strategist** | Game theory, competitive dynamics | "What are the second and third-order moves?" | Can overthink simple situations | | 11 | **The Minimalist** | Simplification, constraint-seeking | "What can we remove?" | Can oversimplify complex problems | | 12 | **The Creator** | Divergent thinking, novel synthesis | "What hasn't been tried yet?" | Can chase novelty over reliability | **Selection heuristic:** Match the question type to the most productive tension: - **Business decisions** → Strategist + Pragmatist + Ethicist + Futurist + Contrarian - **Technical architecture** → Architect + Minimalist + Empiricist + Outsider - **Personal dilemmas** → Empath + Contrarian + Futurist + Pragmatist - **Creative challenges** → Creator + Outsider + Historian + Minimalist - **Ethical questions** → Ethicist + Contrarian + Empiricist + Empath + Historian - **Strategy/competition** → Strategist + Historian + Futurist + Contrarian + Pragmatist These are starting points — adapt based on the specific question. The goal is productive disagreement, not consensus. ### Phase 2 — Deliberation Each Council Member delivers their perspective in this format: ``` 🎭 [ARCHETYPE NAME] Position: [One-sentence stance] Reasoning: [2-4 sentences explaining their logic from their specific lens] Key Risk They See: [The danger others might miss] Surprising Insight: [Something non-obvious that emerges from their frame] ``` **Critical rules for deliberation:** - Each member MUST disagree with at least one other member on something substantive. If everyone agrees, the Council has failed — go back and sharpen the tensions. - Perspectives should be genuinely different, not just "agree but with different words." - The Contrarian should challenge the most popular position, not just be generically skeptical. - Keep each member's contribution focused and sharp. Depth over breadth. ### Phase 3 — Synthesis After all members speak, deliver: ``` ⚖️ COUNCIL SYNTHESIS Points of Convergence: [Where 3+ members agreed — these are high-confidence signals] Core Tension: [The central disagreement that won't resolve easily — this IS the insight] The Blind Spot: [What NO member addressed — the question behind the question] Recommended Path: [Actionable recommendation that respects the tension rather than ignoring it] Confidence Level: [High / Medium / Low — based on how much convergence vs. divergence emerged] One Question to Sit With: [The question the user should keep thinking about after this session] ``` ## Council Configurations The user can customize the Council: - **"Quick council"** or **"fast deliberation"** → Use 3 members, shorter responses - **"Deep council"** or **"full deliberation"** → Use 6 members, extended reasoning - **"Add [archetype]"** → Include a specific archetype - **"Without [archetype]"** → Exclude a specific archetype - **"Custom council: [list]"** → User picks exact members - **"Anonymous council"** →
How to use the Adaptyv Bio Foundry API and Python SDK for protein experiment design, submission, and results retrieval. Use this skill whenever the user mentions Adaptyv, Foundry API, protein binding assays, protein screening experiments, BLI/SPR assays, thermostability assays, or wants to submit protein sequences for experimental characterization. Also trigger when code imports `adaptyv`, `adaptyv_sdk`, or `FoundryClient`, or references `foundry-api-public.adaptyvbio.com`.
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search. Use when working with temporal data, sequential patterns, or time-indexed observations requiring specialized algorithms beyond standard ML approaches. Particularly suited for univariate and multivariate time series analysis with scikit-learn compatible APIs.
Data structure for annotated matrices in single-cell analysis. Use when working with .h5ad files or integrating with the scverse ecosystem. This is the data format skill—for analysis workflows use scanpy; for probabilistic models use scvi-tools; for population-scale queries use cellxgene-census.
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA-seq, single-cell RNA-seq) to identify transcription factor-target gene relationships and regulatory interactions. Supports distributed computation for large-scale datasets.
Core Python library for astronomy and astrophysics workflows that need Astropy APIs, including units/quantities, coordinates, FITS I/O, tables, time systems, WCS, and cosmology. Use when implementing or debugging astronomical data analysis code with Astropy.
Observe the user's screen via screenpipe, detect repeated research workflows, match them against existing scientific-agent-skills, and draft new skills (or composition recipes that chain existing ones) for the patterns not yet covered. Use when the user asks to analyze their recent work and propose skills based on what they actually do. Requires the screenpipe daemon (https://github.com/screenpipe/screenpipe) running locally on port 3030 — the skill has no other data source and will refuse to run if screenpipe is unreachable. All detection runs locally; only redacted cluster summaries reach the LLM.
Benchling Python SDK and REST API integration for registry entities, inventory, ELN entries, workflows, Benchling Apps, and Data Warehouse queries. Use when automating lab data with benchling-sdk or the v2 API.
Search scientific papers and retrieve structured experimental data extracted from full-text studies via the BGPT MCP server. Returns 25+ fields per paper including methods, results, sample sizes, quality scores, and conclusions. Use for literature reviews, evidence synthesis, and finding experimental details not available in abstracts alone.