Safe Share
Use this skill to produce a safe-to-share copy of text. Prefer deterministic local sanitization over model-only guessing.
Workflow
- Confirm the user wants a shareable copy, not a forensic analysis.
- Determine the output mode:
placeholder: best default for docs, issues, READMEs, and tutorialsredact: best when preserving shape is not importantmask: best when keeping a hint of the original value is useful
- Run
scripts/sanitize_text.pyon the exact text the user provided. - Return:
sanitized_textfindings_summaryreview_notes
- Never echo the original sensitive value back to the user.
Operating Rules
- Default to
placeholdermode unless the user asks for something else. - Treat secrets and credentials as higher priority than general PII.
- Replace with stable labels such as
<OPENAI_API_KEY>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