Hypothesis Generation
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
Structures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges.
$ npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install K-Dense-AI/scientific-agent-skills consciousness-council --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/consciousness-council .claude/skills/consciousness-council && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "consciousness-council" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/consciousness-council into .claude/skills/consciousness-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consciousness-council", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/consciousness-councilType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install K-Dense-AI/scientific-agent-skills consciousness-council --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/consciousness-council .agents/skills/consciousness-council && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "consciousness-council" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/consciousness-council into .agents/skills/consciousness-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consciousness-council", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install K-Dense-AI/scientific-agent-skills consciousness-council --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/consciousness-council .cursor/skills/consciousness-council && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "consciousness-council" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/consciousness-council into .cursor/skills/consciousness-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consciousness-council", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/K-Dense-AI/scientific-agent-skills.git --path skills/consciousness-council--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install K-Dense-AI/scientific-agent-skills consciousness-council --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/consciousness-council .gemini/skills/consciousness-council && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "consciousness-council" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/consciousness-council into .gemini/skills/consciousness-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consciousness-council", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install K-Dense-AI/scientific-agent-skills consciousness-councilInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/consciousness-council .github/skills/consciousness-council && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "consciousness-council" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/consciousness-council into .github/skills/consciousness-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consciousness-council", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install K-Dense-AI/scientific-agent-skills consciousness-council --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/consciousness-council .opencode/skills/consciousness-council && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "consciousness-council" agent skill from https://github.com/K-Dense-AI/scientific-agent-skills/tree/main/skills/consciousness-council into .opencode/skills/consciousness-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "consciousness-council", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
consciousness-councilStructures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges.
Consciousness Council is an agent skill from K-Dense-AI/scientific-agent-skills. Structures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges. Simulates thinking archetypes, separates evidence from assumptions and values, and synthesizes a conditional recommendation. Use when the user requests a council, panel, devil's advocate analysis, "mind council", or deliberate comparison of perspectives on a difficult choice.
Its SKILL.md is about 3.5k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/advanced-configurations.md`).
It sits in Research & Science. The repository describes itself as: Turn any AI agent into an AI Scientist. The 1 Agent Skills library for science, used by 250,000+ scientists worldwide. 177 ready-to-use validated skills plus 100+ scientific… The licence is MIT.
3 steps, taken from the step headings in SKILL.md.
Read from SKILL.md and the folder at commit 92ace75. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
arxiv.orgthemindbook.appahkstrategies.netFrom URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Consciousness Council loads about 3.5k tokens when it runs, and up to ~5.1k if it reads all its reference files. Until then it costs about 102 tokens; SKILL.md has 1,552 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from K-Dense-AI/scientific-agent-skills at commit 92ace75, republished under its MIT licence (© K-Dense-AI). 1,552 words, ~3,470 tokens.
.claude/skills/consciousness-council/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.A structured exercise that simulates several thinking archetypes, each emphasizing different assumptions and priorities, then synthesizes their perspectives. These are generated viewpoints from one system, not independent experts or independent evidence. Label factual claims, assumptions, and value judgments separately; verify consequential factual claims against external sources.
Use for a requested comparison of competing priorities or assumptions, including research planning decisions. The output is a decision aid: a conditional recommendation, unresolved questions, and a next step. It does not establish scientific validity by agreement or by the number of perspectives.
This skill runs within the current conversation. It has no bundled code, service API, credentials, or MindBook connection; use the host's available research tools when factual verification is needed. Do not claim that it creates hosted sessions, stores persistent memories, or contacts real experts.
The Council has three phases:
Based on the user's question, select 4–6 Council Members from the archetypes below unless the user requests another configuration. Choose lenses that examine different assumptions, constraints, or values. Agreement supported by the evidence is a valid outcome.
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:
These are starting points — adapt based on the specific question. The goal is to expose decision-relevant trade-offs and evidence gaps without a quota for disagreement or consensus.
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]
Basis: [Which given/verified facts, assumptions, or values support the position]
Key Risk They See: [The danger others might miss]
Decision Check: [Evidence or a changed constraint that would alter this position]Critical rules for deliberation:
After all members speak, deliver:
⚖️ COUNCIL SYNTHESIS
Points of Convergence: [Shared conclusions, with their evidence and assumptions; agreement alone is not a confidence signal]
Core Tension: [The decision-relevant trade-off, or state that no substantive disagreement remains]
Open Question: [An overlooked issue or missing evidence; say if none was identified]
Recommended Path: [Conditional recommendation, next step, and what would change the choice]
Confidence Level: [Qualitative High / Medium / Low with reasons, tied to a specific claim; no percentage inferred from votes or rhetoric]
One Question to Sit With: [The question the user should keep thinking about after this session]Before delivering the synthesis, check that every consequential factual claim traces to the evidence brief, each recommendation respects the constraints, and uncertainties are still visible. A critical unverified premise prevents a high-confidence recommendation. Distinguish confidence in the proposed next step from confidence in the eventual outcome. Record supported agreement and unresolved disagreements; do not resolve them by majority vote.
This is a qualitative review by the agent, not an automated validation gate or proof that the premises are true. Report unresolved checks explicitly.
The user can customize the Council:
See advanced configurations for domain mixes, optional editorial scoring, and bounded multi-round or synthesis-only output.
The Council works best on questions where:
The Council adds less value on:
If the question seems too simple for a full Council, say so — and offer a quick 2-perspective contrast instead.
User: "Quick council: should we run a pilot or begin the full experiment? We have ten weeks and 100 budget units. The pilot costs 20 units and takes two weeks; the full study costs 80 units and takes eight weeks. We don't know whether our assay is reproducible."
This is a fictional, manually worked illustration, not an experimentally validated outcome. The costs, durations, and uncertainty are given facts within the scenario. Assume sequential scheduling, no overlap, and that the pilot would assess the assay conditions needed for the study. Protecting interpretable results is a stated decision priority, not an empirical finding.
| Perspective | Position and basis | Risk and decision check |
|---|---|---|
| Empiricist | Prefer the pilot because assay reproducibility is unknown. Define fit-for-purpose acceptance criteria before observing pilot results. | A pilot using different conditions may not answer the study's question. Change the position if relevant existing validation resolves that uncertainty. |
| Pragmatist | The pilot followed by the full study exactly uses 100 units and ten weeks under the stated assumptions. | There is no contingency for repeats or delays. Check whether the deadline and budget allow a staged decision. |
| Contrarian | Challenge whether this pilot can change the go/no-go decision; if it cannot, redesign it before spending 20 units. | A reassuring pilot could still leave the key uncertainty unresolved. Specify what result would stop or modify the full study. |
Synthesis: All three lenses support resolving the assay uncertainty; this agreement adds no independent evidence. The core tension is learning before commitment versus leaving no schedule or budget margin. The open question is whether the pilot's acceptance criteria can answer the reproducibility question under study conditions. Recommend defining those criteria and a stop rule before committing to either path. Confidence is medium in that next step and low in successful completion of the full study within the current limits. One question to resolve: "Which pilot result would actually change our decision?"
Sensitivity check: If the pilot costs 25 units, the sequential plan costs 105 and is infeasible without a scope or budget change. If relevant assay validation already exists, revisit whether a new pilot is needed. These changes should alter the recommendation even if every archetype initially agreed.
This specific prompt workflow and its optional scoring have not been benchmarked for decision accuracy. Multi-agent studies do not directly validate several voices generated in one conversation. Baltaji et al. (2024) report persona inconsistency and conformity in their tested collaborations. A September 2026 preprint by Ferreira et al. reports that debate did not reliably beat budget-matched sampling in its small-model setting. These bounded findings motivate checking evidence and assumptions; they do not establish a universal benefit or failure of council exercises.
Originally created by AHK Strategies, with inspiration from MindBook. The current MindBook FAQ, reviewed 2026-09-30, distinguishes its 12-archetype Council Chamber from a separate six-mind Mind Council. This repository's standalone exercise retains its own 3/4–6/6-perspective configurations; it is not a client for either hosted feature.
© K-Dense-AI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 1 other file (references) in skills/consciousness-council of K-Dense-AI/scientific-agent-skills.
Open the folder on GitHubat commit 92ace75
We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in K-Dense-AI/scientific-agent-skills, which our catalogue first saw on October 7, 2026.
Consciousness Council next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Consciousness Council this skillK-Dense-AI/scientific-agent-skills | 48k | 1 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Hypothesis Generationspacering-net/codeg | 3.9k | 14 repos | ~3.6k | Automated safety check: Notes | MIT | |
| GitHub Deep Researchbytedance/deer-flow | 84k | 4 repos | ~1.3k | Automated safety check: Pass | MIT | |
| Nature Paper CardYuan1z0825/nature-skills | 47k | 2 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 | |
| Content Research Writerweapp-tailwindcss/weapp-tailwindcss | 1.9k | 25 repos | ~3.5k | Automated safety check: Pass | MIT | |
| Last30daysmvanhorn/last30days-skill | 64k | — | ~7.9k | Automated safety check: Notes | MIT |
spacering-net/codeg
Structured hypothesis formulation from observations. An agent skill from spacering-net/codeg.
bytedance/deer-flow
Researches a GitHub repository over four rounds using the GitHub API and web search, then writes a structured markdown report with timeline, metrics and Mermaid diagrams.
Yuan1z0825/nature-skills
Builds a structured deep-reading card for one scientific paper, covering methods, how experiments support claims, limitations and research ideas, with a script to prepare the source.
weapp-tailwindcss/weapp-tailwindcss
Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section.
mvanhorn/last30days-skill
Research what people actually say about any topic in the last 30 days.
spacering-net/codeg
Structured manuscript/grant review with checklist-based evaluation.
K-Dense-AI/scientific-agent-skills
Estimates reaction fluxes inside cells from steady-state carbon-13 labeling data with a bundled mfapy-based solver, and reports which fluxes the data pin down.
K-Dense-AI/scientific-agent-skills
Plans, runs, and documents analytical method validation, verification, or transfer studies under ICH Q2(R2)/Q14, USP, ICH M10, CLSI EP, or ISO/IEC 17025.
K-Dense-AI/scientific-agent-skills
Runs Cantera constant-volume or constant-pressure ignition simulations and reports temperature-based ignition delay with mechanism provenance and checks.
K-Dense-AI/scientific-agent-skills
Predicts how small molecules bind to a protein with DiffDock, covering batch docking, pose ranking by confidence and checks on the results; not for binding affinity.
K-Dense-AI/scientific-agent-skills
Plans and audits runs of the HypoGeniC and HypoRefine packages, which propose hypotheses from labeled text datasets, with local checks before any model call.
K-Dense-AI/scientific-agent-skills
Organizes scope, controlled documents, risk files and traceability into draft evidence for human review against ISO 13485, 14971, 17025 and 15189.
Categories
Structures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges. Consciousness Council is an agent skill from K-Dense-AI/scientific-agent-skills. Structures a multi-perspective council exercise for decisions, research trade-offs, and creative challenges.
Consciousness Council fits situations like: the user requests a council; devils advocate analysis; deliberate comparison of perspectives on a difficult choice.
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a claude-code`. Or copy the skill folder (skills/consciousness-council in K-Dense-AI/scientific-agent-skills) into .claude/skills/consciousness-council in your project. Claude Code loads it when a task matches its description.
Run `npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a codex`. Or copy the skill folder (skills/consciousness-council in K-Dense-AI/scientific-agent-skills) into .agents/skills/consciousness-council in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add K-Dense-AI/scientific-agent-skills --skill consciousness-council -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/consciousness-council, .gemini/skills/consciousness-council, .github/skills/consciousness-council and .opencode/skills/consciousness-council in your project.
SKILL.md names no scripts, command-line tools or credentials: Consciousness Council is instructions for the agent only.
SKILL.md names 3 domains. As links in the text: arxiv.org, themindbook.app and ahkstrategies.net. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Consciousness Council is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.5k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 1.7k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Consciousness Council: Hypothesis Generation (spacering-net/codeg, 3.9k stars), GitHub Deep Research (bytedance/deer-flow, 84k stars), Nature Paper Card (Yuan1z0825/nature-skills, 47k stars) and Content Research Writer (weapp-tailwindcss/weapp-tailwindcss, 1.9k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
K-Dense-AI (a GitHub organization) maintains it in K-Dense-AI/scientific-agent-skills, which has 48,215 GitHub stars. The repository holds 153 skills in this directory. The repository was last updated on October 5, 2026.
Source: K-Dense-AI/scientific-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.