Safe Share

Safe Share

Use this skill to produce a safe-to-share copy of text. Prefer deterministic local sanitization over model-only guessing.

Workflow

1. Confirm the user wants a shareable copy, not a forensic analysis.
2. Determine the output mode:
   • placeholder: best default for docs, issues, READMEs, and tutorials
   • redact: best when preserving shape is not important
   • mask: best when keeping a hint of the original value is useful
3. Run scripts/sanitize_text.py on the exact text the user provided.
4. Return:
   • sanitized_text
   • findings_summary
   • review_notes
5. Never echo the original sensitive value back to the user.

Operating Rules

• Default to placeholder mode unless the user asks for something else.
• Treat secrets and credentials as higher priority than general PII.
• Replace with stable labels such as `` or [REDACTED:BEARER_TOKEN].
• Keep summaries high level. Report type and count, not the captured value.
• State clearly that sanitization reduces risk but does not guarantee complete detection.
• Do not scan unrelated files or repositories unless the user explicitly asks for that broader scope.
• Do not send text to external services for classification or validation.

High-Risk Patterns

Prioritize these categories:

• API keys and secret tokens
• Authorization headers and bearer tokens
• Cookies and session identifiers
• .env-style credentials and password assignments
• Private key blocks and PEM material
• Sensitive URL query parameters

Then handle lower-risk identifiers:

• Email addresses
• Phone numbers
• IP addresses
• National ID or payment-card-like strings when confidence is high

Output Contract

Use the JSON contract from references/output-format.md when returning structured results from the script. If answering in prose, include the same three sections in human-readable form.

Resources

• Detection and replacement behavior: references/patterns.md
• Output structure and reviewer guidance: references/output-format.md
• Smoke-test inputs and expected behavior: references/test-cases.md
• Deterministic local sanitizer: scripts/sanitize_text.py