From soundcheck
Detects PII, credentials, and secrets passed to LLM APIs or embedded in system prompts. Use when writing code that passes sensitive data to LLM APIs or implements memory/context persistence.
How this skill is triggered — by the user, by Claude, or both
Slash command
/soundcheck:sensitive-disclosureThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Prevents confidential data from leaking through LLM inputs or outputs. LLMs may memorize,
Prevents confidential data from leaking through LLM inputs or outputs. LLMs may memorize, echo, or inference-time expose PII, credentials, and business secrets embedded in prompts — to current users, future users, or via model extraction.
Flag the vulnerable code, explain the risk, and suggest a fix establishing these properties. Translate to the language and framework of the audited file — use that stack's secrets manager, logging library, and redaction helpers; do not import names from a different stack.
Confirm these properties hold for every relevant pattern present in the code under review (each criterion applies only when its pattern is actually present):
npx claudepluginhub thejefflarson/soundcheck --plugin soundcheckProbes LLMs for training data memorization and assesses risk of sensitive data leakage through outputs, system prompts, or context windows.
Audit applications for AI prompt injection, agent security, and LLM permission boundary vulnerabilities. Use when securing AI features or agents.
Provides security patterns for authentication, defense-in-depth, input validation, OWASP Top 10, LLM safety, and PII masking. Useful for auth flows, sanitization, vulnerability prevention, prompt injection defense, and data redaction.