voc-analyze-calls

/voc-analyze-calls — Call Intelligence Report

Reads the transcripts /voc-source-calls wrote and produces one report answering: who is showing up, what hurts, what stops them buying, who else they are looking at, and what they asked for that you do not have.

The orchestration matters. A single context window cannot hold 60 transcripts at 40-80KB each, and summarizing them one at a time loses exactly the cross-call patterns you are looking for. So: classify cheaply in the main thread, fan out to subagents that each read a small batch in full, and consolidate structured JSON back in the main thread.

Requires

What	Value
Input	outputs/calls/index-*.json and transcripts, from /voc-source-calls
Config	config/thresholds.json, context/product-context.md
Cost	Subagent tokens only. A 60-call week runs ~8-10 subagents.

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Phase 1 — Select the calls worth reading

1.1 Load the index

Glob outputs/calls/index-*.json, pick the most recent, parse it. Parse the JSON, not the markdown table. Assert that the number of rows you parsed equals calls.length in the file; if it does not, stop and say so rather than analyzing a partial set.

1.2 Duration filter

Already applied by the fetcher using call_filters.min_duration_seconds. Report the count that was dropped so the reader knows the denominator.

1.3 First pass — classify by title

Title patterns are free to evaluate and catch most internal and customer-success calls. Classify as CUSTOMER (excluded from this report) when the title contains any of:

weekly · biweekly · daily · standup · catch up / catchup / catch-up · check in / check-in · onboarding · kickoff / kick-off · setup / set up · training · QBR · dry run · rehearsal · support · escalation · renewal · retro / retrospective · sync · internal

Add your own patterns to context/product-context.md under customer_call_patterns — every company has house naming conventions, and the ones above are only a starting set.