How do I install the Multi Model Synthesis skill?

Run npx skillmds@latest add tf-worldone/multi-model-synthesis in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Multi Model Synthesis safe to use?

This skill has not completed SkillMD's automated safety review yet. Capability flags: executes scripts. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Multi Model Synthesis?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Multi Model Synthesis free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Multi Model Synthesis?

TF-WorldOne (@tf-worldone) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Multi Model Synthesis by tf-worldone

Name: Multi Model Synthesis
Rating: 4.666666666666667 (3 reviews)
Author: TF-WorldOne

Multi Model Synthesis

Run a selectable multi-model independent answer panel and synthesize the results. Use when the user asks for multiple top models, a model council, parallel opinions, GPT 5.5 Pro plus Opus/DeepSeek/GLM/Gemini comparison, or a single final answer produced from independent model outputs without a debate/discussion round. Supports model selection, available-model filtering, partial success, retries, cost/token logging, and configurable synthesizers.

TF-WorldOne Updated Sep 22, 2026

File contents

TawabaranPro - Synth Model

Use this skill to send one user task to selected model APIs in parallel, collect independent answers, and have a configurable synthesizer produce the final synthesis.

Panel

Use these LiteLLM API model routes and roles:

gpt-5.5: GPT 5.5 Pro respondent.
opus-4.8-max: Claude Opus 4.8 at max reasoning effort.
deepseek-v4-pro: DeepSeek V4 Pro respondent.
glm-5.2: GLM 5.2 respondent.
gemini-3.1-pro-deep-think: Gemini 3.1 Pro Preview with high thinking level for Deep Think behavior.
default synthesizer: gpt-5.5, overridable with --synthesizer.

Workflow

Run the helper script instead of manually launching each model:

py ".\skills\multi-model-synthesis\scripts\run_panel.py" --prompt "USER TASK HERE"

Choose models and synthesizer:

py ".\skills\multi-model-synthesis\scripts\run_panel.py" --prompt "USER TASK HERE" --models opus-4.8-max,gemini-3.1-pro-deep-think --synthesizer opus-4.8-max

For long prompts or prompts with quotes, write the task to a temporary text file and run:

py ".\skills\multi-model-synthesis\scripts\run_panel.py" --prompt-file "C:\path\to\task.txt"

The script starts the local LiteLLM router if needed, checks /v1/models, filters out models missing local API keys or LiteLLM registrations, calls usable respondent model APIs in parallel, saves raw outputs under %USERPROFILE%\.codex\tmp\multi-model-synthesis\, then calls the selected synthesizer with fallback synthesizers if needed. Use CODEX_MULTI_MODEL_ROUTER_SCRIPT or CODEX_MULTI_MODEL_LITELLM_CONFIG to override the bundled router script or LiteLLM config.

Use --dry-run to inspect planned models without chat completions. Use --retries, --timeout, --allow-partial, --synthesizer-fallbacks, --price-config, and --max-cost-usd for reliability and cost control.

Run artifacts include final.md, report.md, metadata.json, run.json, models/*.md, raw/*.response.json, and errors/*.log.

Output Rules

Do not add a debate, critique, or second discussion round.
Preserve each model answer as an independent source for the synthesis.
Return the selected synthesizer's final answer as the main answer.
Mention any model that failed only when the script reports a failure.
Use the same language as the user's task unless the task asks otherwise.

Failure Handling

If one respondent fails, continue with available successful answers by default. If the selected synthesizer fails, try fallback synthesizers. If all synthesizers fail, report the saved output directory and return the successful respondent answers manually.

---name: multi-model-synthesisdescription: Run a selectable multi-model independent answer panel and synthesize the results. Use when the user asks for multiple top models, a model council, parallel opinions, GPT 5.5 Pro plus Opus/DeepSeek/GLM/Gemini comparison, or a single final answer produced from independent model outputs without a debate/discussion round. Supports model selection, available-model filtering, partial success, retries, cost/token logging, and configurable synthesizers.---# TawabaranPro - Synth ModelUse this skill to send one user task to selected model APIs in parallel, collect independent answers, and have a configurable synthesizer produce the final synthesis.## PanelUse these LiteLLM API model routes and roles:- `gpt-5.5`: GPT 5.5 Pro respondent.- `opus-4.8-max`: Claude Opus 4.8 at max reasoning effort.- `deepseek-v4-pro`: DeepSeek V4 Pro respondent.- `glm-5.2`: GLM 5.2 respondent.- `gemini-3.1-pro-deep-think`: Gemini 3.1 Pro Preview with high thinking level for Deep Think behavior.- default synthesizer: `gpt-5.5`, overridable with `--synthesizer`.## WorkflowRun the helper script instead of manually launching each model:```powershellpy ".\skills\multi-model-synthesis\scripts\run_panel.py" --prompt "USER TASK HERE"```Choose models and synthesizer:```powershellpy ".\skills\multi-model-synthesis\scripts\run_panel.py" --prompt "USER TASK HERE" --models opus-4.8-max,gemini-3.1-pro-deep-think --synthesizer opus-4.8-max```For long prompts or prompts with quotes, write the task to a temporary text file and run:```powershellpy ".\skills\multi-model-synthesis\scripts\run_panel.py" --prompt-file "C:\path\to\task.txt"```The script starts the local LiteLLM router if needed, checks `/v1/models`, filters out models missing local API keys or LiteLLM registrations, calls usable respondent model APIs in parallel, saves raw outputs under `%USERPROFILE%\.codex\tmp\multi-model-synthesis\`, then calls the selected synthesizer with fallback synthesizers if needed. Use `CODEX_MULTI_MODEL_ROUTER_SCRIPT` or `CODEX_MULTI_MODEL_LITELLM_CONFIG` to override the bundled router script or LiteLLM config.Use `--dry-run` to inspect planned models without chat completions. Use `--retries`, `--timeout`, `--allow-partial`, `--synthesizer-fallbacks`, `--price-config`, and `--max-cost-usd` for reliability and cost control.Run artifacts include `final.md`, `report.md`, `metadata.json`, `run.json`, `models/*.md`, `raw/*.response.json`, and `errors/*.log`.## Output Rules- Do not add a debate, critique, or second discussion round.- Preserve each model answer as an independent source for the synthesis.- Return the selected synthesizer's final answer as the main answer.- Mention any model that failed only when the script reports a failure.- Use the same language as the user's task unless the task asks otherwise.## Failure HandlingIf one respondent fails, continue with available successful answers by default. If the selected synthesizer fails, try fallback synthesizers. If all synthesizers fail, report the saved output directory and return the successful respondent answers manually.

Frequently asked questions