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ingest-user-interview

Analyze a user interview from Granola, pasted text, or a file into an evidence-backed briefing, journey insights, product findings, patterns, and actions. Use for /ingest user-interview, onboarding interviews, research calls, or requests to process user feedback.

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egregore-labs/egregore293 stars(GitHub 293 + cccskills 0)

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Files included (2)

  • SKILL.md3.0 KB
  • references/analysis-contract.md4.4 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Ingest user interview

Acquire the transcript, understand the research intent, analyze it with appropriate lenses, preview the result, then persist one approved typed package through Egregore Runtime.

Read references/analysis-contract.md before analysis or package construction.

When to invoke

Analyze a user interview from Granola, pasted text, or a file into an evidence-backed briefing, journey insights, product findings, patterns, and actions. Use for /ingest user-interview, onboarding interviews, research calls, or requests to process user feedback.

Use the meeting skill for a general team meeting.

Source

Accept one of:

  • Granola connector: search/select, then fetch transcript and stable metadata;
  • pasted transcript;
  • a user-authorized .txt, .md, or .json file.

Infer participant, researcher, interview type, date, and source revision when reliable; otherwise ask compact questions. Do not put connector credentials or the raw transcript into canonical memory merely to analyze it.

Context and analysis

Reuse sufficient EGREGORE_ORG_CONTEXT_V1. Open selected canonical evidence through Runtime when verification is necessary. If cross-interview comparison is requested and context is insufficient, make at most one Egregore retrieval request. Never query graph/QMD directly; canonical Markdown/Git wins.

Start with a compact scaffold. Analyze inline for short interviews. For long or complex material, parallel Journey, Sentiment, and Product lenses may run once, then synthesize their evidence and disagreements. Do not force multi-agent work when it adds latency without analytical value.

Show the emotional arc, evidence-backed product reading, proposed durable insights, confidence, priority, tensions, and researcher actions. Ask Save, Edit, or Skip. Do not write before Save.

Canonical writeback

Build one temporary egregore-research-ingest/v1 package under tmp/ containing the approved interview briefing, participant journey document where needed, and typed findings/patterns/decisions. Then make exactly one deterministic call, using {package-json} for the package file just written:

bash bin/research-ingest.sh interview --input '{package-json}'

Runtime owns authorization, schema/path validation, stable identity, provenance, canonical Markdown, Git provenance, derived-index refresh, background embedding, and telemetry. Do not separately create directories, append indexes, write files, run /save, or manage graph projection.

Report accepted/partial/rejected status and canonical paths. Cross-interview synthesis reads canonical artifacts; graph is optional enrichment only. Publication and notifications are separate later effects and require their own explicit approval.

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