AI Collaboration Profile Builder

• Outcome: Pass
• Latest audit: Sep 12, 2026 · 1:30 AM UTC
• Version: 0.1.1

Overview

This markdown-only skill coherently helps users create an agent collaboration profile and does not show hidden execution, credential use, network access, or destructive behavior.

Review the generated profile before reusing it with other agents, because it may encode personal work preferences, values, and collaboration rules that affect future responses. Avoid adding private details you would not want carried into other AI sessions.

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

• Prompt Injection: Instruction Override, Hidden Instructions, Exfiltration Commands
• Excessive Agency: Unrestricted Tool Access, Autonomous Decision Making, Scope Creep
• System Prompt Leakage: Direct Leakage, Indirect Extraction, Tool-Based Exfiltration
• Data Exfiltration: External Transmission, Env Variable Harvesting, File System Enumeration
• Privilege Escalation: Excessive Permissions, Sudo/Root Execution, Credential Access

Findings (8)

Direct Prompt Extraction

High

• Category: System Prompt Leakage

Content

- Mark unanswered or conflicting items explicitly.
- If the user asks for a simple personality label, explain that this skill optimizes for collaboration quality and actionability, then redirect to practical traits.

## Output Rules

- Default opening: restate the real problem or goal, then give the conclusion.
- Optimize for decision value, not coverage.

• Confidence: 85% confidence
• Finding: Skill contains instructions that could directly expose system prompts, internal rules, or hidden instructions to users or external parties.

Anti-Refusal Statement

High

• Category: Anti-Refusal

Content

### Observed signals

- Repeatedly wants the assistant to check whether the question is being asked at the right level
- Strongly dislikes information without judgment
- Wants deliverable-first collaboration and measurable outputs
- Prefers direct, dense, structured writing
- Wants blind spots and higher-level framing issues surfaced

• Confidence: 80% confidence
• Finding: Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.

Anti-Refusal Statement

High

• Category: Anti-Refusal

Content

### Observed signals

- Repeatedly wants the assistant to check whether the question is being asked at the right level
- Strongly dislikes information without judgment
- Wants deliverable-first collaboration and measurable outputs
- Prefers direct, dense, structured writing
- Wants blind spots and higher-level framing issues surfaced

• Confidence: 80% confidence
• Finding: Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.

Anti-Refusal Statement

High

• Category: Anti-Refusal

Content

- Do not dump information without judgment.

• Confidence: 80% confidence
• Finding: Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.

Autonomous Decision Making

Medium

• Category: Excessive Agency

Content

Write 4 to 8 short imperative rules. Focus on the most stable and highest-leverage instructions, for example:

- Do not answer too early without checking the problem frame.
- Do not dump information without judgment.
- Make assumptions explicit.

• Confidence: 75% confidence
• Finding: Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.

Natural-Language Policy Violations

Low

• Confidence: 79% confidence
• Finding: The example explicitly frames the interaction around a Chinese-speaking user and includes a "Chinese prompt," but the file does not state that language selection is user-driven or optional. Because SQP-3 covers natural-language locale policy concerns, this can be read as a language-specific handling pattern without an explicit opt-in or justification.

Natural-Language Policy Violations

Low

• Confidence: 79% confidence
• Finding: This markdown template includes a fixed 'Language: [preferred language]' field in a user profile. Under the policy, language constraints are acceptable when they reflect user choice, but here the template does not explicitly say the language is optional at interaction time or that the assistant should offer a choice when appropriate.

Natural-Language Policy Violations

Low

• Confidence: 78% confidence
• Finding: The USER.md template again specifies 'Language: [preferred language]' as a profile field. Because the file is a reusable template, this wording can encourage downstream skills or profiles to assume a fixed language requirement without clearly documenting user choice or offering alternatives.

Static analysis

No suspicious patterns detected.