v1.0.0

HFT Paper Trader — Autonomous Crypto Framework

BenignClawScan verdict for this skill. Analyzed May 1, 2026, 5:55 AM.

Analysis

This appears to be a coherent paper-trading simulation skill, with disclosed but noteworthy autonomous/bulk simulated-trade behavior and local state files.

GuidanceBefore installing or using it, confirm you want a paper-only trading workflow, set clear limits on symbols and trade volume, and review the local portfolio, ledger, and lessons files it creates or updates. Do not connect real exchange credentials unless you have separately audited and constrained any added trading code.

Findings (2)

Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.

Abnormal behavior control

Checks for instructions or behavior that redirect the agent, misuse tools, execute unexpected code, cascade across systems, exploit user trust, or continue outside the intended task.

Tool Misuse and Exploitation

SeverityLowConfidenceHighStatusNote

SKILL.md

Use hft-paper-trader to scan the watchlist and trade all signals

This shows the skill may ask the agent to perform bulk simulated trading actions across multiple assets. It is aligned with the paper-trading purpose, but users should bound how much the agent runs.

User impactIf invoked broadly, the agent may make many simulated trades, API lookups, and local ledger updates, though the artifacts do not show real-money trading authority.

RecommendationUse explicit limits such as paper-only mode, maximum trades, symbols, and time windows before asking it to scan and trade all signals.

Sensitive data protection

Checks for exposed credentials, poisoned memory or context, unclear communication boundaries, or sensitive data that could leave the user's control.

Memory and Context Poisoning

SeverityLowConfidenceHighStatusNote

SKILL.md

Self-improvement loop: lessons.md updated after each loss

The skill stores persistent trading lessons that may influence later decisions. This is disclosed and purpose-aligned, but persistent notes can become stale or misleading.

User impactFuture paper-trading runs could rely on accumulated lessons or logs that may not be accurate or may reflect a bad prior run.

RecommendationPeriodically review, edit, or clear lessons.md and related portfolio or ledger files before relying on future trading simulations.