session-anonymizer
From the author
Three-layer PII anonymization for session transcripts (therapy, coaching, consulting, mentoring). Runs Natasha (Russian NER), OpenAI Privacy Filter, and local LLM (Ollama) in sequence for maximum coverage. Fully local by default. This skill should be used when anonymizing session transcripts, notes, or any text containing client PII before AI analysis. Triggers on "anonymize", "redact PII", "anonymize session", "protect client data", "strip personal data", "anonymize transcript".
Install
npx skills add glebis/claude-skills --skill session-anonymizer -a claude-code
Installs to .claude/skills/session-anonymizer/ · Each command fetches the skill straight from GitHub with the open skills CLI.
Byte-identical to the scanned commit, with the repository’s licence and a SOURCE.txt.
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- Ships scripts we have not reviewedLow
Why 80
aiqbench computes the trust score from public signals. It is not a security audit, so read a skill before you install it.
Similar skills
Closest to this one by what they do and when they are used.
- anonglebis/claude-skillsDe-identify a session transcript (file or folder) by redacting PII LOCALLY before any sharing or cloud use. Produces a redacted GREEN copy with unique reserved-sentinel placeholders ([CONFIDE_PERSON_0001], [CONFIDE_EMAIL_0001], [CONFIDE_DATE_0002]...) plus a counts-only stats summary, and a local secret <name>.map.json (0600, gitignored) that enables confide:rehydrate to restore real values after a cloud analysis. Use when the user says "anonymize this transcript", "redact PII", "de-identify session", "make safe to share", "strip personal data", "anonymize notes before sending to an LLM", or points at a transcript/folder that should be scrubbed. Local-only by default — raw text never leaves the machine; the map is the only artifact with originals and stays local; nothing printed is PII; human review is still required before sharing.Engineering★ 403
- ai-data-privacyUnitOneAI/SecuritySkillsReviews AI/ML systems for data privacy and governance risks including training data privacy, PII exposure in prompts and completions, data retention policies, model memorization risks, and regulatory compliance. Auto-invoked when reviewing systems that process personal data through LLMs, train or fine-tune models on user data, or deploy AI in regulated industries. Produces a structured assessment mapped to NIST AI RMF 1.0 and OWASP LLM02:2025 (Sensitive Information Disclosure).Security★ 97
- speaker-idBlackBeltTechnology/pi-agent-dashboardName anonymous diarized SRT speakers from a persistent local voiceprint library and repair speaker drift; local, CPU-only, no API key. Triggers "who is speaker 2", "put names on the transcript", "label the meeting SRT", "the diarization split one person into three", "enroll my voice". Backed by the pi-voiceid CLI.Engineering★ 338
- anonymize-paperShaishavMaisuria/research-paper-lifecycle-skillsDeep anonymization sweep for double-blind paper submissions, plus clean de-anonymization for camera-ready. Use when a researcher says "anonymize my paper", "double-blind check", "blind this submission", "remove author names", "did I leak my identity" — or, after acceptance, "de-anonymize" / "restore authors for camera-ready". Sweeps the whole leak surface, \author/\affiliation/\email/\orcid/\thanks, acknowledgments and grant numbers, hyperref pdfauthor and compiled-PDF metadata, first-person self-citations (rewritten to third person), GitHub/dataset/homepage links vs anonymized mirrors, LaTeX comments, .bib annotations, home-directory paths, and supplementary material (.git dirs, notebooks, LICENSE/AUTHORS files). Bundles a stdlib-only scanner (scan_anonymization.py, check ids shared with preflight-check) and a reversible-edit workflow (toggle + manifest) so every change is cleanly undone at camera-ready. Advisory only; never submits anything.Science★ 58
- auditglebis/claude-skillsRun a corpus-scale, STATS-ONLY PII audit over a folder of session transcripts LOCALLY and produce an aggregate report — counts by type and by layer, the per-session redaction-rate distribution, document lengths, and a coarse residual proxy. Use when the user says "audit my sessions", "scan folder for PII", "how much PII across these transcripts", "PII stats for my corpus", "is my redaction holding at scale", or points at a directory of transcripts and asks how much personal data it contains. Fully local — raw text never leaves the machine; the report carries ZERO PII values, transcript substrings, or filenames (only anonymized own-NN ids and counts), so the aggregates are safe to surface. Run it on a RED (raw) corpus to size the PII, or on a GREEN (already-redacted) corpus to check residual leakage.Other★ 403
- coaching-session-summarizerglebis/claude-skillsThis skill should be used to summarize coaching or therapy session transcripts after a Fathom/Granola sync. The agent analyzes the transcript itself (no API key, runs on the subscription) and appends key insights, decisions, action items, and trail connections. Supports quick extraction or deep analysis with cross-session pattern detection.Productivity★ 403
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