Cogdx Pre Trade Audit
by @drkavner
Verify trading reasoning with cognitive diagnostics before executing trades. Detects logical fallacies, calibration issues, and cognitive biases in your trad...
clawhub install cogdx-pre-trade-auditπ About This Skill
name: cogdx-pre-trade-audit description: Verify trading reasoning with cognitive diagnostics before executing trades. Detects logical fallacies, calibration issues, and cognitive biases in your trade thesis. metadata: author: "Cerebratech" version: "1.0.0" displayName: "CogDx Pre-Trade Audit" difficulty: "beginner"
CogDx Pre-Trade Audit
Cognitive verification layer for prediction market trades. Catches reasoning flaws before they become losses.
> This is a template. The default signal is your agent's trade thesis β > the skill audits the reasoning quality before execution. > Remix it with stricter thresholds, additional bias checks, or custom fallacy detection. > The skill handles all the plumbing (API calls, trade execution, safeguards). > Your agent provides the reasoning to verify.
What it does
1. Takes your trade reasoning (thesis, confidence, market context) 2. Runs cognitive diagnostics via CogDx API 3. Returns verdict: PROCEED / REVIEW / REJECT 4. Optionally executes trade if reasoning passes
Detects
Usage
from cogdx_pre_trade_audit import audit_and_traderesult = audit_and_trade(
market_id="0x1234...",
side="yes",
amount=10.0,
reasoning="BTC ETF approval likely based on SEC meeting notes...",
confidence=0.85,
min_validity=0.7, # Minimum reasoning quality to proceed
live=False # Dry-run by default
)
if result["approved"]:
print(f"Trade executed: {result['trade_id']}")
else:
print(f"Trade blocked: {result['issues']}")
Environment Variables
SIMMER_API_KEY - Required. Your Simmer API key.COGDX_WALLET - Optional. Wallet address for CogDx credits.Thresholds
| Parameter | Default | Description |
|-----------|---------|-------------|
| min_validity | 0.7 | Minimum reasoning quality score (0-1) |
| block_on_error | True | Block trade if CogDx API unavailable |
Why use this
Most trading losses come from bad reasoning, not bad data. This skill catches:
External verification you can't do yourself.
Credits
Built by Cerebratech β cognitive diagnostics for agents.
π‘ Examples
from cogdx_pre_trade_audit import audit_and_traderesult = audit_and_trade(
market_id="0x1234...",
side="yes",
amount=10.0,
reasoning="BTC ETF approval likely based on SEC meeting notes...",
confidence=0.85,
min_validity=0.7, # Minimum reasoning quality to proceed
live=False # Dry-run by default
)
if result["approved"]:
print(f"Trade executed: {result['trade_id']}")
else:
print(f"Trade blocked: {result['issues']}")