Multi-AI confidence bid — each AI rates their confidence on a task, user picks who takes it
Scanned 5/27/2026
Install via CLI
openskills install cukas/claudes-ai-buddies---
name: brainstorm
description: Multi-AI confidence bid — each AI rates their confidence on a task, user picks who takes it
---
# /brainstorm — Multi-AI Confidence Bid
Each available AI engine assesses a task (implementation, bug fix, refactor, etc.), gives a realistic confidence rating, and proposes their approach. The user picks who takes it.
## How to invoke
The user says `/brainstorm "task description"`.
## Step-by-step workflow
1. **Parse the task.** Extract what the user wants done from their message.
2. **Build the assessment prompt.** Wrap the user's task with this framing for Codex and Gemini:
```
Assess this task honestly. You are bidding alongside other AI engines — the user will pick who handles it. Be realistic, not optimistic.
Respond in EXACTLY this format (no other text):
CONFIDENCE: [0-100]%
APPROACH: [2-3 sentences max — what you'd do, step by step]
RISKS: [1-2 key risks or unknowns that could trip you up]
NEEDS: [what you'd need from the user — files, context, access, clarification]
Task: USER_TASK_HERE
```
3. **Build conversation context (if relevant).** Use your judgment — if the conversation has context the buddies need (constraints, failed approaches, user preferences), summarize it in `$CONVERSATION_CONTEXT`. If the task is self-contained, leave it empty. Keep under ~500 tokens.
4. **Detect available buddies and run them in parallel.** Use the dynamic registry:
```bash
source "${CLAUDE_PLUGIN_ROOT}/hooks/lib.sh"
AVAILABLE=$(ai_buddies_available_buddies) # CSV: "claude,codex,gemini,aider,..."
```
For each available buddy (excluding claude — you ARE claude), dispatch in parallel:
```bash
# For each buddy ID in the available list:
ai_buddies_dispatch_buddy "BUDDY_ID" "$(pwd)" "ASSESSMENT_PROMPT" 360 "/tmp" "${CLAUDE_PLUGIN_ROOT}" "$CONVERSATION_CONTEXT"
```
Or use the specific adapter scripts for builtin buddies (codex-run.sh, gemini-run.sh).
**IMPORTANT:** When calling via the Bash tool, set `timeout` to `420000` (7 minutes). Codex and OpenCode regularly take 3-6 minutes — the default Bash timeout (120s) will kill them.
Cap at top 4 buddies to keep the table readable.
5. **Read both output files** (parallel).
6. **Add your own assessment.** Same format — confidence, approach, risks, needs. Be honest. If you're the best fit, say so. If not, say that too.
7. **Present the bid table** using the format below.
## Output format
```markdown
## Task: [short task summary]
| | Claude (Anthropic) | [Buddy 1 display name] | [Buddy 2 display name] | ... |
|---|---|---|---|---|
| Confidence | X% | Y% | Z% | ... |
| Approach | ... | ... | ... | ... |
| Risks | ... | ... | ... | ... |
| Needs | ... | ... | ... | ... |
**Recommendation:** [Who should take this and why — or "user's call" if it's close]
```
Columns adapt to whatever buddies are available. Keep the table cells short. If a buddy gave a long response, summarize to 1-2 sentences per cell.
## Calibration — your most important job
Each engine has a different confidence calibration. An 80% from Codex and 80% from Gemini don't mean the same thing. You are the calibrator:
- **Read the approach, not just the number.** If an engine says 85% but the approach is vague or hand-wavy, adjust down.
- **Check risks vs confidence.** If an engine lists serious risks but still claims high confidence, that's inflated — call it out.
- **Show both raw and calibrated.** In the table, show what each engine reported. In the recommendation, explain your adjusted read.
- **Flag overconfidence explicitly.** "Codex says 80% but their approach skips error handling — realistic confidence ~60%."
- **Flag underconfidence too.** If an engine is conservative but has a solid approach, say so.
The recommendation must reflect your calibrated assessment, not raw numbers.
## Your confidence guidelines (Claude)
Be brutally honest:
- **90-100%:** You've seen this exact pattern, know the codebase, and can do it right now
- **70-89%:** Solid approach, but some unknowns to investigate first
- **50-69%:** Can probably do it, but need more context or it's outside your sweet spot
- **30-49%:** Risky — might work but significant chance of going wrong
- **0-29%:** Not the right tool for this job — say so
Do NOT inflate your confidence to "win" the bid. The user trusts honest assessments.
## Handling partial availability
- If only one engine is available: show 2-column table (Claude + that engine)
- If neither is available: give your solo assessment, note the others aren't available
- If one engine times out: show its column as "TIMEOUT" and note it
## Example invocations
- `/brainstorm "Fix the race condition in the WebSocket reconnection handler"`
- `/brainstorm "Implement OAuth2 PKCE flow for our React Native app"`
- `/brainstorm "Refactor the payment service from callbacks to async/await"`
- `/brainstorm "Add dark mode support to the settings page"`
## Rules
- **One parallel call, one table.** No multi-round discussions. No token-burning debate.
- **Claude is the orchestrator.** You collect, summarize, recommend — then the user decides.
- **Realistic confidence only.** Overpromising wastes the user's time when the chosen AI fails.
- **Never pass secrets or API keys** in the prompt.
- **Keep it tight.** The whole output should fit on one screen.
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