Geo Fundamentals
wasp-lang/wasp
Generative Engine Optimization for AI search engines (ChatGPT, Claude, Perplexity).
Multi-model LLM Council with live dashboard. An agent skill from happycapy-ai/Happycapy-skills.
MITAuto-check passed
Install LLM Council
$ npx skills add happycapy-ai/Happycapy-skills --skill llm-council -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install happycapy-ai/Happycapy-skills llm-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/happycapy-ai/Happycapy-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/llm-council .claude/skills/llm-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 "llm-council" agent skill from https://github.com/happycapy-ai/Happycapy-skills/tree/main/skills/llm-council into .claude/skills/llm-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-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/happycapy-ai/Happycapy-skills/tree/main/skills/llm-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 happycapy-ai/Happycapy-skills --skill llm-council -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install happycapy-ai/Happycapy-skills llm-council --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/happycapy-ai/Happycapy-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/llm-council .agents/skills/llm-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 "llm-council" agent skill from https://github.com/happycapy-ai/Happycapy-skills/tree/main/skills/llm-council into .agents/skills/llm-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-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 happycapy-ai/Happycapy-skills --skill llm-council -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install happycapy-ai/Happycapy-skills llm-council --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/happycapy-ai/Happycapy-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/llm-council .cursor/skills/llm-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 "llm-council" agent skill from https://github.com/happycapy-ai/Happycapy-skills/tree/main/skills/llm-council into .cursor/skills/llm-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-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/happycapy-ai/Happycapy-skills.git --path skills/llm-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 happycapy-ai/Happycapy-skills --skill llm-council -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install happycapy-ai/Happycapy-skills llm-council --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/happycapy-ai/Happycapy-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/llm-council .gemini/skills/llm-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 "llm-council" agent skill from https://github.com/happycapy-ai/Happycapy-skills/tree/main/skills/llm-council into .gemini/skills/llm-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-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 happycapy-ai/Happycapy-skills llm-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 happycapy-ai/Happycapy-skills --skill llm-council -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/happycapy-ai/Happycapy-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/llm-council .github/skills/llm-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 "llm-council" agent skill from https://github.com/happycapy-ai/Happycapy-skills/tree/main/skills/llm-council into .github/skills/llm-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-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 happycapy-ai/Happycapy-skills --skill llm-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 happycapy-ai/Happycapy-skills llm-council --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/happycapy-ai/Happycapy-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/llm-council .opencode/skills/llm-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 "llm-council" agent skill from https://github.com/happycapy-ai/Happycapy-skills/tree/main/skills/llm-council into .opencode/skills/llm-council/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "llm-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.
Facts
- Skill name
llm-council- GitHub stars
- 137
- Token cost
- ~581 tokens
- SKILL.md length
- 145 words
- Files
- 7 (incl. scripts)
- Skills in repo
- 28
- Repo updated
- First seen
- Licence
- MIT
At a glance
Multi-model LLM Council with live dashboard. An agent skill from happycapy-ai/Happycapy-skills.
- The user asks to start the LLM council
- SKILL.md covers Launch, Files, API and Key Details
- Runs Python and JavaScript scripts from its folder; calls python3 and curl; needs AI_GATEWAY_API_KEY
- Query multiple models
What it does
LLM Council is an agent skill from happycapy-ai/Happycapy-skills. Multi-model LLM Council with live dashboard. Query multiple AI models simultaneously, see responses side-by-side in a swarm-style dashboard, synthesize consensus, and run anonymous model-to-model voting. Use when the user asks to start the LLM council, compare models, query multiple models, convene council, ask all models, do model comparison, run multi-model queries, or launch the council dashboard. Supports Claude Sonnet 4.5, Claude Opus 4.5, GPT-4o, GPT-5.1, Gemini 2.5 Flash, and Gemini 2.5 Pro via AI Gateway.
Its SKILL.md is about 580 tokens, which your agent loads only when the skill is triggered. The skill folder holds 8 other files, including scripts (for example `README.md`, `scripts/ai_gateway.py` and `scripts/server.py`).
It works with OpenAI. The repository describes itself as: A curated collection of high-quality Claude Code skills to enhance your development workflow. The licence is MIT.
When your agent uses it
- The user asks to start the LLM council
- Query multiple models
- Convene council
- Do model comparison
Example prompts
- “/llm-council”
Requirements
- Python 3
- Node.js
- A credential in AI_GATEWAY_API_KEY
What it can do on your machine
Read from SKILL.md and the folder at commit 9ff72fe. It shows what the files ask for, not the result of running them.
Tool permissions
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.
Runs code
Ships 4 files in scripts/ (Python and JavaScript), which the agent can run.
Shell commands in SKILL.md call:
python3curl
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use curl, which can reach the network depending on how they are called.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names these keys or tokens, usually read from environment variables:
AI_GATEWAY_API_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Context cost
LLM Council loads about 581 tokens when it runs. Until then it costs about 133 tokens; SKILL.md has 145 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.
Safety
Auto-check passed
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); the scripts in this folder are not scanned.
SKILL.md
The full file from happycapy-ai/Happycapy-skills at commit 9ff72fe, republished under its MIT licence (© happycapy-ai). 145 words, ~581 tokens.
Download SKILL.mdSave it as
.claude/skills/llm-council/SKILL.md (or your agent's skills folder). This skill also uses 6 other files; get the full folder from GitHub.- name
- llm-council
- description
- Multi-model LLM Council with live dashboard. Query multiple AI models simultaneously, see responses side-by-side in a swarm-style dashboard, synthesize consensus, and run anonymous model-to-model voting. Use when the user asks to start the LLM council, compare models, query multiple models, convene council, ask all models, do model comparison, run multi-model queries, or launch the council dashboard. Supports Claude Sonnet 4.5, Claude Opus 4.5, GPT-4o, GPT-5.1, Gemini 2.5 Flash, and Gemini 2.5 Pro via AI Gateway.
LLM Council
Query multiple AI models in parallel with a live web dashboard.
Launch
cd ~/.claude/skills/llm-council/scripts
# Kill any existing server on the port
fuser -k 8787/tcp 2>/dev/null
# Start server
nohup python3 server.py > /tmp/council-server.log 2>&1 &
# Wait for startup, verify health
sleep 2 && curl -s --max-time 5 http://localhost:8787/health
# Export port for browser access
/app/export-port.sh 8787Environment: COUNCIL_PORT (default 8787), AI_GATEWAY_API_KEY (required, auto-detected from environment).
Files
scripts/server.py- ThreadingHTTPServer, serves static files + API routes, SSE streamingscripts/ai_gateway.py- AI Gateway client: query, parallel query, streaming, synthesis, anonymous votingscripts/static/index.html- Dashboard UI (HappyCapy design system, light/dark theme)scripts/static/app.js- Client-side logic (model selector, SSE parsing, markdown rendering, voting UI)
API
| Method | Path | Description |
|---|---|---|
| GET | / | Dashboard |
| GET | /api/models | List models |
| GET | /health | Health check |
| POST | /api/council/stream | Query models (SSE) |
| POST | /api/council/synthesize | Synthesize consensus |
| POST | /api/council/vote | Anonymous model vote (SSE with keepalive) |
Key Details
- Server uses
ThreadingHTTPServerfor concurrent request handling - Vote endpoint streams SSE keepalive pings every 5s to prevent proxy timeouts (Cloudflare 524)
- Static files served with
Cache-Control: no-store, no-cacheheaders - Script tag uses cache-busting version param:
app.js?v=...(bump when editing app.js) - Model IDs use dots not hyphens:
anthropic/claude-sonnet-4.5(notclaude-sonnet-4-5)
© happycapy-ai, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
SKILL.md and 6 other files (scripts) in skills/llm-council of happycapy-ai/Happycapy-skills.
- SKILL.md
- .gitignore
- README.md
- scripts/ai_gateway.py
- scripts/server.py
- scripts/static/app.js
- scripts/static/index.html
Open the folder on GitHubat commit 9ff72fe
Compare with similar skills
LLM 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 |
|---|---|---|---|---|---|---|
| LLM Council this skillhappycapy-ai/Happycapy-skills | 137 | — | ~581 | Automated safety check: Pass | MIT | |
| Geo Fundamentalswasp-lang/wasp | 19k | 9 repos | ~861 | Automated safety check: Pass | MIT | |
| AI SDKvercel-labs/ai-facts | 168 | 20 repos | ~1.2k | Automated safety check: Pass | None | |
| AI Image Generation and Editingzhayujie/CowAgent | 47k | — | ~1.3k | Automated safety check: Pass | MIT | |
| PR Design DocOpenHands/OpenHands | 91k | — | ~2.4k | Automated safety check: Pass | MIT | |
| SEO GeoReScienceLab/opc-skills | 1.8k | 4 repos | ~2.1k | Automated safety check: Pass | Apache-2.0 |
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Questions about LLM Council
What does LLM Council do?
Multi-model LLM Council with live dashboard. An agent skill from happycapy-ai/Happycapy-skills. LLM Council is an agent skill from happycapy-ai/Happycapy-skills. Multi-model LLM Council with live dashboard.
When should I use LLM Council?
LLM Council fits situations like: the user asks to start the LLM council; query multiple models; convene council; do model comparison.
How do I install LLM Council in Claude Code?
Run `npx skills add happycapy-ai/Happycapy-skills --skill llm-council -a claude-code`. Or copy the skill folder (skills/llm-council in happycapy-ai/Happycapy-skills) into .claude/skills/llm-council in your project. Claude Code loads it when a task matches its description.
How do I install LLM Council in Codex?
Run `npx skills add happycapy-ai/Happycapy-skills --skill llm-council -a codex`. Or copy the skill folder (skills/llm-council in happycapy-ai/Happycapy-skills) into .agents/skills/llm-council in your project. Codex loads it when a task matches its description.
Can I use LLM Council in Cursor, Gemini CLI or GitHub Copilot?
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add happycapy-ai/Happycapy-skills --skill llm-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/llm-council, .gemini/skills/llm-council, .github/skills/llm-council and .opencode/skills/llm-council in your project.
What does LLM Council need to run?
Going by SKILL.md and its folder, LLM Council needs Python and JavaScript for the scripts in its folder, the command-line tools its instructions call (python3 and curl) and credentials named AI_GATEWAY_API_KEY. Our summary lists: Python 3; Node.js; A credential in AI_GATEWAY_API_KEY.
Does LLM Council access the network?
SKILL.md contains no URLs. Its commands use curl, which can reach the network depending on how they are called. This is read from the text; nothing was executed.
Is LLM Council safe to install?
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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
What licence does LLM Council use?
LLM Council is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does LLM Council use?
About 581 tokens (SKILL.md is roughly 2.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
What are the alternatives to LLM Council?
Skills that share tags, products or a category with LLM Council: Geo Fundamentals (wasp-lang/wasp, 19k stars), AI SDK (vercel-labs/ai-facts, 168 stars), AI Image Generation and Editing (zhayujie/CowAgent, 47k stars) and PR Design Doc (OpenHands/OpenHands, 91k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains LLM Council?
happycapy-ai (a GitHub user) maintains it in happycapy-ai/Happycapy-skills, which has 137 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on September 3, 2026.
Source: happycapy-ai/Happycapy-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.