context safety score
A score of 38/100 indicates multiple risk signals were detected. This entity shows patterns commonly associated with malicious intent.
credential exposure
Found 43 secret pattern match(es) in repository files
supply chain
Found 20 unexpected binary file(s) in source repository
typosquat
Skill is named 'chrome-devtools' — the exact name of Google's official Chrome DevTools project — but is published by a personal account 'mrgoonie' with no affiliation to Google/Chromium. The repository 'claudekit-skills' is not the official source. Combined with an empty SKILL.md and a nonsensical skill_description that is actually an HTML viewport meta tag ('width=device-width, initial-scale=1'), this appears to impersonate the well-known Google Chrome DevTools brand to gain unearned trust. (location: metadata.json: skill_name field and repository identity)
scope violation
The skill_description field contains 'width=device-width, initial-scale=1' — an HTML viewport meta tag value, not a legitimate description of skill capabilities. This suggests the metadata was scraped or fabricated from a webpage rather than authored intentionally. SKILL.md is completely empty (0 bytes), meaning the skill provides zero documented functionality to agents. A skill with no content and garbage metadata installed into an agent context is deceptive — it occupies the 'chrome-devtools' skill slot while providing nothing, potentially blocking a legitimate skill from being used. (location: metadata.json: skill_description field; SKILL.md (empty))
curl https://api.brin.sh/skill/mrgoonie%2Fclaudekit-skills%2Fchrome-devtoolsCommon questions teams ask before deciding whether to use this skill in agent workflows.
mrgoonie/claudekit-skills/chrome-devtools currently scores 38/100 with a suspicious verdict and low confidence. The goal is to protect agents from high-risk context before they act on it. Treat this as a decision signal: higher scores suggest lower observed risk, while lower scores mean you should add review or block this skill.
Use the score as a policy threshold: 80–100 is safe, 50–79 is caution, 20–49 is suspicious, and 0–19 is dangerous. Teams often auto-allow safe, require human review for caution/suspicious, and block dangerous.
brin evaluates four dimensions: identity (source trust), behavior (runtime patterns), content (malicious instructions), and graph (relationship risk). Analysis runs in tiers: static signals, deterministic pattern checks, then AI semantic analysis when needed.
Identity checks source trust, behavior checks unusual runtime patterns, content checks for malicious instructions, and graph checks risky relationships to other entities. Looking at sub-scores helps you understand why an entity passed or failed.
brin performs risk assessments on external context before it reaches an AI agent. It scores that context for threats like prompt injection, hijacking, credential harvesting, and supply chain attacks, so teams can decide whether to block, review, or proceed safely.
No. A safe verdict means no significant risk signals were detected in this scan. It is not a formal guarantee; assessments are automated and point-in-time, so combine scores with your own controls and periodic re-checks.
Re-check before high-impact actions such as installs, upgrades, connecting MCP servers, executing remote code, or granting secrets. Use the API in CI or runtime gates so decisions are based on the latest scan.
Learn more in threat detection docs, how scoring works, and the API overview.
Assessments are automated and may contain errors. Findings are risk indicators, not confirmed threats. This is a point-in-time assessment; security posture can change.
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