Install
openclaw skills install multisageQuery Multisage for multi-expert AI answers from Claude, GPT, and Gemini. Use this skill whenever the user wants multiple AI perspectives on a question, says "ask multisage", "multisage this", "get expert opinions", wants a multi-AI consultation, or needs a well-rounded answer that considers different viewpoints. Also use for deep research queries that need comprehensive analysis from multiple AI providers in parallel.
openclaw skills install multisageQuery the Multisage API for multi-expert AI answers. Multisage sends your question to Claude, GPT, and Gemini simultaneously, then synthesizes their responses into a single, well-rounded answer — highlighting where they agree, disagree, and what unique insights each provides.
The multisage CLI must be installed globally:
npm install -g multisage
An API key is required. Get one at https://multisage.ai/settings (under "API Keys").
Before running any multisage command, you must ensure MULTISAGE_API_KEY is available in your shell. The env var is often NOT inherited automatically — check and load it explicitly:
# 1. Check if it's already set
echo "${MULTISAGE_API_KEY:0:8}"
# 2. If empty, look for it in common locations
grep MULTISAGE_API_KEY .env 2>/dev/null || grep MULTISAGE_API_KEY ~/.env 2>/dev/null
# 3. Export it (replace with actual key found above)
export MULTISAGE_API_KEY="msk_..."
If you get a timeout or authentication error, the most likely cause is a missing API key — always verify it's set before debugging further.
When running multisage from Claude or any non-interactive context, always use the -q flag to suppress the interactive spinner (doesn't render in tool output).
Redirect output to a file with > instead of piping through tee, which can cause issues in non-TTY contexts:
# Correct — redirect to file
multisage -q "your question" > /tmp/multisage-output.txt 2>&1
cat /tmp/multisage-output.txt
# Wrong — tee can cause issues in non-TTY contexts
multisage -q "your question" | tee output.txt # DON'T DO THIS
For most questions, run a standard query. This consults all three AI providers and returns a synthesized answer with stage breakdown:
multisage -q "your question here"
The default output shows each stage: quick answer, expert synthesis, and debate (if the experts disagree). This costs 1 credit.
For questions that need thorough, in-depth analysis — research topics, complex technical questions, literature reviews — use deep research mode. This launches 3 parallel deep research sessions (one per provider) and synthesizes the results:
multisage -q --deep-research "your question here"
Deep research costs 5 credits and takes 5-25 minutes. The CLI streams progress updates as each provider completes. You can detach with Ctrl+C and check results later.
| Flag | What it does |
|---|---|
-q | Suppress spinner (always use from Claude) |
-f, --full | Show everything: quick answer, individual expert responses, synthesis, debate |
--final-only | Show only the final synthesized answer (skip stages) |
-j, --json | Output as structured JSON |
--deep-research | Use deep research mode (5 credits, 5-25 min) |
Combine flags as needed. For example, -f -q gives full output without a spinner. -j gives structured JSON (useful if you need to parse the response programmatically).
Deep research runs asynchronously. If you start one and need to check on it later:
# Check if results are ready
multisage results <threadId>
# Cancel an in-progress query
multisage cancel <threadId>
The threadId is printed when you start a deep research query.
multisage -q "...") — Good for most questions. Quick (30-90 seconds), costs 1 credit. Best for factual questions, advice, comparisons, code help.multisage -q --deep-research "...") — For thorough analysis. Each provider does its own deep research with web search, then results are cross-referenced and synthesized. Best for research topics, technical deep-dives, market analysis, literature reviews.# Standard query — redirect to file, then read
multisage -q "What are the tradeoffs between SQLite and PostgreSQL for a hobby project?" > /tmp/ms-output.txt 2>&1
cat /tmp/ms-output.txt
# Full output (includes individual expert responses)
multisage -q -f "What are the tradeoffs between SQLite and PostgreSQL for a hobby project?" > /tmp/ms-output.txt 2>&1
cat /tmp/ms-output.txt
# Deep research
multisage -q --deep-research "What are the latest advances in protein folding prediction?"
# JSON output for parsing
multisage -q -j "Is Rust or Go better for CLI tools?" > /tmp/ms-output.txt 2>&1
cat /tmp/ms-output.txt | jq '.answer'
The API returns:
answer — Final synthesized answerexperts — List of expert names (or full details with -f)creditsUsed — Credits consumed (1 for standard, 5 for deep research)stages.quickAnswer — Initial quick answer before expert consultationstages.synthesis — Synthesized answer incorporating all expert perspectivesstages.debate — Debate section highlighting disagreements (null if experts agree)msk_| Status | Meaning |
|---|---|
| 401 | Invalid or missing API key |
| 402 | Insufficient credits — purchase at https://multisage.ai/pricing |
| 429 | Rate limited or too many concurrent requests (check Retry-After header) |
| 500 | Server error — try again |
Timeout errors are almost always caused by a missing API key — the CLI makes an unauthenticated request that hangs instead of returning a clean error. Fix: verify MULTISAGE_API_KEY is exported (see API Key Setup above).
Diagnostic checklist (run these before retrying):
# Is the API key set?
[ -n "$MULTISAGE_API_KEY" ] && echo "Key set: ${MULTISAGE_API_KEY:0:8}..." || echo "KEY NOT SET"
# Is the CLI installed?
which multisage && multisage -V
# Quick connectivity test
multisage -q "hello" > /tmp/ms-test.txt 2>&1 && echo "OK" || echo "FAILED — check output:" && cat /tmp/ms-test.txt