# Aoa Sanitized Share

> aoa-sanitized-share

- Skill: `majiayu000/aoa-sanitized-share` (Agent Skill, multi-file: 2 files)
- Install (CLI): `npx skillmds@latest add majiayu000/aoa-sanitized-share`
- Raw SKILL.md: https://api.skillmd.com/api/skills/majiayu000/aoa-sanitized-share/raw
- Safety review: pending (external: skill-scanner PASS, skillspector PASS)
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Security
- Author: majiayu000 (https://skillmd.com/u/majiayu000)
- Updated: 2026-09-21
- Page: https://skillmd.com/skills/majiayu000/aoa-sanitized-share

---


# aoa-sanitized-share

## Intent

Use this skill to turn potentially sensitive technical material into a shareable, reviewable, public-safe form.

## Trigger boundary

Use this skill when:
- logs, configs, diagnostics, reports, or examples may contain sensitive details
- a result needs to be shared publicly or with a broader audience
- raw material may reveal secrets, topology, internal identifiers, or unsafe context

Do not use this skill when:
- the material is already clearly public-safe and minimal
- the task is to perform the underlying operational change rather than prepare a shareable surface
- the main task is deciding whether the underlying action should be allowed; use `aoa-approval-gate-check`
- the task is to preview or execute the operational change itself; use `aoa-dry-run-first` or `aoa-safe-infra-change`

## Inputs

- material to be shared
- sharing audience or context
- known sensitive surfaces
- acceptable level of abstraction

## Outputs

- sanitized shareable artifact, abstract summary, or recommendation not to share the raw material directly
- note on what was generalized or removed
- warning about any remaining ambiguity or sensitive edge

## Procedure

1. inspect the material for secrets, tokens, private paths, topology, internal identifiers, or unsafe operational detail
2. remove, redact, or generalize sensitive details
3. preserve the technical lesson or signal without preserving the sensitive surface
4. note what kind of sanitization was applied when that matters for interpretation
5. verify that the shared result remains useful without revealing what should stay private

## Contracts

- shareable output should not leak secrets or private infrastructure detail
- sanitization should preserve meaning where possible
- generalization should not silently change the core lesson beyond recognition
- uncertainty about sensitivity should lean toward caution

## Risks and anti-patterns

### Failure modes

- over-sanitizing until the artifact becomes meaningless
- under-sanitizing because a value looks harmless in isolation

### Negative effects

- the shared artifact becomes hard to reuse or verify
- sensitivity leaks through topology, naming, or surrounding context even when tokens are removed

### Misuse patterns

- sharing raw excerpts when a bounded summary would be safer
- treating a small harmless-looking field as proof that the full material is safe

### Detection signals

- the sanitized output still points too directly to private topology or naming
- a reviewer cannot tell what was generalized or removed
- the artifact no longer communicates the lesson it was meant to preserve

### Mitigations

- generalize paths, hostnames, and private identifiers when needed
- name the sanitization level and the remaining uncertainty
- verify the shared result remains useful without preserving the sensitive surface

## Verification

- confirm obvious sensitive surfaces were checked
- confirm the resulting artifact is still understandable
- confirm the sanitization level matches the intended audience
- confirm raw sensitive detail was not preserved by accident
- confirm remaining uncertainty is named rather than ignored

## Technique traceability

Manifest-backed techniques:
- AOA-T-PENDING-SANITIZED-SHARE from `8Dionysus/aoa-techniques` at `TBD` using path `TBD` and sections: Intent, When to use, Inputs, Outputs, Core procedure, Contracts, Risks, Validation

## Adaptation points

Future project overlays may add:
- local sanitization rules
- examples of sensitive surfaces
- public versus private sharing thresholds
- project-specific reporting conventions