Reinforced Thinking Mode

• Outcome: Pass
• Latest audit: Sep 11, 2026 · 10:55 AM UTC
• Version: 1.1.0

Overview

This is a coherent file-based thinking workflow, but users should know it creates local analysis files and deletes intermediate drafts by default.

Install only if you want a heavier workflow that writes problem and round files in the workspace. If you need to audit or keep intermediate reasoning, tell the agent to preserve the intermediate files before using the skill.

A.I.G

Vulnerability Patterns

• Skill Instruction Hijacking: Alters the agent's session goals or safety constraints when the skill loads
• Agent Memory Poisoning: Writes attacker-controlled rules into memory that affect later sessions
• Remote Payload Retrieval and Execution: Fetches external code whose behavior can change after review
• Embedded Malicious Code: Ships malicious scripts inside the skill and executes them locally
• Unauthorized Access and Privilege Escalation: Obtains permissions beyond the task's legitimate needs

SkillSpector

Vulnerability Patterns

• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep
• Trigger Abuse: Overly Broad Trigger, Shadow Command Trigger, Keyword Baiting Trigger
• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access

Findings (8)

Missing User Warnings

High

• Confidence: 98% confidence
• Finding: The skill directs automatic deletion of intermediate files and retention of only the final report, again without explicit warning or consent. In context this is more dangerous because the deleted files may contain user inputs, intermediate reasoning artifacts, or evidence needed for audit, debugging, or recovery, and the deletion is autonomous rather than user-confirmed.

Vague Triggers

Medium

• Confidence: 92% confidence
• Finding: The activation criteria are broad and keyword-driven, which can cause the skill to trigger on normal analytical requests that did not explicitly ask for this workflow. In this skill's context, unintended invocation can lead to unnecessary file operations, autonomous multi-round processing, and behavior the user did not clearly consent to.

Missing User Warnings

Medium

• Confidence: 95% confidence
• Finding: The skill instructs the agent to create a directory and write problem data to disk without any user-facing warning or consent gate. Silent file creation is risky because it changes the workspace state, may store sensitive prompt content, and can surprise users who expected analysis to remain in-memory.

Autonomous Decision Making

Medium

• Category: Excessive Agency

Content

### Phase 4: Cleanup

Automatically delete intermediate files (problem.md, round_*.md), only keep final_report.md.

If retention needed, specify in), only keep final prompt.

• Confidence: 97% confidence
• Finding: The phrase 'Automatically delete intermediate files' delegates a consequential workspace decision to the agent without requiring user approval. Autonomous destructive actions are dangerous because they can remove useful or sensitive artifacts, reduce transparency, and prevent users from reviewing what the system did before data is destroyed.

Vague Triggers

Medium

• Confidence: 94% confidence
• Finding: The activation conditions are broad and match common requests like deep analysis, evaluation, design, and planning, so this skill can be invoked unintentionally in many normal conversations. Because the skill changes workflow substantially and triggers file creation, multi-round processing, and later cleanup, accidental activation can lead to unnecessary actions, user surprise, and execution of behaviors the user did not explicitly request.

Missing User Warnings

Medium

• Confidence: 97% confidence
• Finding: The skill instructs automatic deletion of intermediate files and only mentions retention as an opt-in detail, without a prominent user-facing warning at the point of activation or before deletion. This creates a risk of unintended data loss, especially because the intermediate files may contain valuable reasoning, notes, or user-provided content that the user expects to inspect or preserve.

Natural-Language Policy Violations

Low

• Confidence: 90% confidence
• Finding: The language support section states that English is the primary language and Chinese is merely 'available,' which signals a preferred enforced locale rather than a user-selected option. The policy for this audit flags language or locale constraints when they are not presented as an explicit choice or justified regional limitation.

Natural-Language Policy Violations

Low

• Confidence: 73% confidence
• Finding: The description and all user-facing instructions are presented exclusively in Chinese, with no indication that users may choose another language. Under the stated policy, forcing a specific language without opt-in can be a natural-language policy issue unless the locale restriction is documented and justified.

Static analysis

No suspicious patterns detected.