# Feature Usage Feed

> Set up an LLM-judge evaluation that extracts canonical use cases for a PostHog feature at scale and streams the results to a Slack channel as a live feed. Use when someone wants to understand how users are actually using a specific AI/LLM-powered feature in production — what they're investigating, what questions they're trying to answer, and what patterns surface — without manually reading hundreds of traces. Assumes the feature emits $aigeneration and $aievaluation events with $sessionid linkage to the trigger user's recording (the standard setup post the session-summary linkage PRs).

## Facts
- Page: https://tashan.sh/capability/skill-posthog-feature-usage-feed
- tashan id: skill:PostHog/feature-usage-feed
- Source: https://github.com/PostHog/skills
- Type: skill
- Category: devtools
- tashan score: not scored (catalogued only — too little public evidence)
- Adoption: 9.0
- Upkeep: 96.0
- Freshness: 92.0
- Evidence coverage: 84% of the inputs this score can use
- Health: active
- Instruction depth: not yet graded
- Official: no

## Install

```sh
cp -r feature-usage-feed ~/.claude/skills/
```

## Security audit
Not scanned. We audit npm-published capabilities; this one has no npm package we can resolve, or has not reached the queue. This is not a clean bill of health.

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Measured 2026-08-20 by tashan (https://tashan.sh) from public evidence. Scorer s5.