Incident Response & Digital Forensics Eval
==========================================

Status: failed
Score: 66/100
Risk: high
Decision: do_not_auto_install
Policy: block
Reason: Audit score: Risky

Install:
npx skills add Masriyan/Claude-Code-CyberSecurity-Skill --skill Incident Response & Digital Forensics

Required checks:
- PASS Task fit: Task wording matches this skill metadata.
- PASS Install path: Install handoff is available.
- PASS Install command safety: standard package or runtime install path
- WARN Trust score: Potentially useful, but at least one trust signal needs human inspection.
- FAIL Audit score: Risky
- FAIL Agent safety gate: This skill should not be selected by an agent without explicit human security review.
- PASS License clarity: MIT
- FAIL Permission surface: secrets or environment access, shell or command execution

Warnings:
- Trust score: Potentially useful, but at least one trust signal needs human inspection.
- Audit risk risky exceeds max_risk=medium
- High-risk permission hints: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
- Permission surface may require sandboxing
- Potential broker, wallet, exchange, or real-money execution surface; sandbox and explicit approval are required
- evidence_collector.py truncates at ~400 lines, likely incomplete implementation
- timeline_builder.py also appears truncated, missing full implementation
- SKILL.md mentions 'Frameworks' metadata field but none are declared in frontmatter
- This skill may touch real-money trading, broker, wallet, or exchange operations; use only in a sandbox with explicit approval.
- Quality score needs review
- Permission surface needs review: secrets or environment access, shell or command execution

Validation plan:
1. Inspect repository, README/SKILL.md, license, and recent commits before production use.
2. Install in an isolated workspace or sandbox with no production secrets available.
3. Run the smallest representative task and record files touched, commands run, network access, and outputs.
4. Compare the selected skill against at least one alternative when the eval status is review or failed.
5. Promote only after the agent reports a successful verification result and unresolved warnings are accepted.

Do not use when:
- teams that need a vendor-supported SLA
- production agents without a repository review
- evidence_collector.py truncates at ~400 lines, likely incomplete implementation
- No OpenAgentSkill engagement data yet
- Audit risk risky exceeds max_risk=medium
- High-risk permission hints: Shell or command execution, Secrets or environment access
- Dependency or permission surface needs review
- Permission surface may require sandboxing

URLs:
- Skill: https://www.openagentskill.com/skills/masriyan-incident-response-digital-forensics
- Audit: https://www.openagentskill.com/skills/masriyan-incident-response-digital-forensics/audit
- JSON: https://www.openagentskill.com/api/agent/evals?slug=masriyan-incident-response-digital-forensics