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@e307415
by shingo imotasimota/agent-skills85 stars
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Conducting user research: interview guides, usability test plans, qualitative analysis, persona creation, journey mapping. Use when research design or analysis is needed; complements Echo.

Use this Skill: https://skilld.dev/gh/simota/agent-skills/field

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referenceai-assisted-research.md

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AI-Assisted Research & Synthetic Users

Purpose: Define where AI helps research, where it does not, and how to use synthetic users safely. Contents: current adoption signals, AI role split, synthetic-user guardrails, decision flow, risk checklist.

Current Signals

Signal Value
Researchers citing AI analysis/synthesis as a top trend 88%
Researchers seeing synthetic users as impactful 48%
Time reduction from AI-assisted qualitative analysis up to 80%
Synthetic agents mimicking survey answers in some studies up to 85%

Role Split

  • AI handles what: transcription, clustering, coding suggestions, draft structure.
  • Humans handle why and what to do: empathy, judgment, ethics, prioritization, strategic interpretation.

Synthetic Users: Use And Non-Use

Do Don't
Use for preparation or hypothesis generation Use as a replacement for real-user research
Treat outputs as hypotheses to validate Present synthetic output as user evidence
Use with widely documented user groups Use with niche or specialized populations
Pilot interview guides or proto-journeys Use for final concept validation

Decision Flow

Use synthetic users only when all are true:

  • the target group is broadly documented
  • the task is preparation, desk research, or early hypothesis generation
  • stakeholders are unlikely to mistake it for real research
  • a real-user validation step is planned

Otherwise: use real-user research.

Risk Checklist

Risk Mitigation
Hallucinated patterns Verify against source data
Bias amplification Use diverse source material and bias checks
Privacy leakage Anonymize data before AI processing
Skill atrophy Keep periodic manual analysis in the workflow
Loss of human nuance Keep interviews and final interpretation human-led

Field Usage By Phase

Phase Acceptable AI use Hard boundary
DEFINE Summarize prior research Verify summary accuracy
DESIGN Pilot guides or synthesize assumptions Do not skip human study design review
ANALYZE Assist coding and pattern detection Validate against source data
SYNTHESIZE Draft structure Human owns final narrative
DISTILL Trend summarization Human owns calibration

Source: SKILL.md on GitHub

No alerts13d3 checks · Risk SAFE
  • Gen Agent Trust Hub13d

    The skill provides a comprehensive and professional framework for user research operations. It emphasizes ethical data handling, participant privacy, and systematic analysis methodologies. While the skill processes external data, which is an inherent surface for indirect prompt injection in LLMs, it lacks high-risk capabilities like code execution or file system modification, and includes multiple human-in-the-loop guardrails to ensure output integrity.

  • Socket13d

    No alerts

  • Snyk13d

    Risk: LOW · No issues

Signed by skilld at e307415. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

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Activeupdated 2 weeks ago

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