Audit persona panels for under-represented groups and rate their material impact.
npx skills add https://github.com/NOMARJ/sigil --skill silence-audit
Please help me install this Agent Skill. Skill: silence-audit Source: https://github.com/NOMARJ/sigil/tree/main/packs/discovery/skills/silence-audit Command: npx skills add https://github.com/NOMARJ/sigil --skill silence-audit
Persona panels and internet-sourced evidence routinely over-represent vocal, English-speaking, tech-literate, and urban populations while under-representing groups whose absence can materially skew product decisions; this skill makes those omissions visible, assesses their impact, and prescribes mitigation paths so teams do not mistake majority internet signals for the whole population.
Run a silence-audit on the current persona panel to identify missing groups, rate their material impact, and generate mitigation actions.
High-intent search queries and answers about installing and using this skill.
A silence audit detects under-represented groups in persona panels by inventorying present evidence sources and highlighting missing demographics. It rates the material impact of these omissions as HIGH, MED, or LOW to prevent skewed product decisions.
A silence audit in user research is a structured review that reveals missing voices in your evidence base. It enumerates present and absent source types, assesses the impact of under-represented groups, and recommends mitigation steps like seeking alternative data sources.
Assessing bias impact in an evidence panel involves checking for commonly under-represented groups such as older adults, low-income users, and rural populations. The audit rates the material impact of these missing groups to determine if majority signals mask the whole population.
Run a blind spot audit on personas during the DISCOVER workflow after persona construction. This prevents product features from being validated exclusively against a skewed evidence base that over-represents vocal, English-speaking, and tech-literate populations.
Mitigate missing evidence sources in persona panels by labeling limitations, seeking alternative evidence like census or NGO reports, or flagging the gap as a fieldwork priority. The audit generates a structured report with actionable mitigation paths per missing group.
Persona bias materially affects product decisions when evidence over-represents tech-literate, urban populations while ignoring non-tech users. The audit quantifies this impact and outputs a blind spot rating to highlight risks of validating features against skewed internet signals.
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