Multisage
v2.2.0Query 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...
Like a lobster shell, security has layers — review code before you run it.
Multisage Skill
Query 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.
Prerequisites
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").
API Key Setup (Do This First)
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.
Running from Claude (Important)
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
Standard Query
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.
Deep Research
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.
Output Options
| 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).
Managing Deep Research
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.
When to Use Which Mode
- Standard (
multisage -q "...") — Good for most questions. Quick (30-90 seconds), costs 1 credit. Best for factual questions, advice, comparisons, code help. - Deep Research (
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.
Typical Usage from Claude
# 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'
Response Structure
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)
Limits and Errors
- Questions are truncated to 1000 characters
- 5-minute timeout for standard queries
- API keys must start with
msk_ - Rate limit: 10 requests/minute, 3 concurrent
| 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 |
Troubleshooting
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
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