thinking-model-enhancer

ReviewAudited by ClawScan on May 10, 2026.

Overview

Prompt-injection indicators were detected in the submitted artifacts (you-are-now); human review is required before treating this skill as clean.

This looks safe to install if you want a local thinking/memory helper. Be aware that it stores summaries and learning data under ~/.claude/thinking_models, so avoid sensitive inputs or clear the stored memory when needed. Also review and approve any repair commands or scripts it recommends before running them. ClawScan detected prompt-injection indicators (you-are-now), so this skill requires review even though the model response was benign.

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.

What this means

Private decision prompts or summaries could remain on disk and be reused in future thinking-model runs.

Why it was flagged

The memory manager writes thinking snapshots to a persistent local directory; the same file defines snapshots with problem summaries, output summaries, and key findings.

Skill content
self.memory_dir = Path.home() / ".claude" / "thinking_models" / "memory" ... json.dump(snapshot.to_dict(), f, ensure_ascii=False, indent=2)
Recommendation

Avoid entering secrets or highly sensitive details unless you are comfortable with local retention, and periodically clear or review the ~/.claude/thinking_models memory files.

What this means

Following recommended repair actions without review could change files, configuration, or services outside the thinking skill itself.

Why it was flagged

The diagnostic workflow can recommend executing fixes or creating repair scripts, which is coherent for troubleshooting but can affect a user's system if followed blindly.

Skill content
High (>90%) | Multiple sources confirm, tested solution | Recommend immediate execution ... Last Resort: Create temporary fix script (only if all else fails)
Recommendation

Treat these as advisory recommendations; require explicit user approval, review generated scripts, and test changes before running them on important systems.