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Join raw platform metrics JSONL back to registry/manifest metadata and compute experiment scoring priors.
Install with Codex or Claude Copy this prompt, paste it into Codex, Claude, or another assistant, and let it review the skill page and install it for you.
Based on SOC occupation classification
Optional polish + scoring of a draft before publish, and engagement scoring after.
Generate a Broadcast Kit content-batch contract from Markdown, a directory, a repo path, or a publish registry.
Fetch and normalize platform metrics into the Broadcast Kit metrics snapshot shape.
Interview the user's content-publishing goal, map it to a capability tier, recommend the minimum setup, then run the matching recipe from CATALOG.md. Use this skill for any "publish / grow / analyze on Douyin / XHS / X" request.
Publish one Douyin manifest via the in-package Playwright publisher.
Publish a tweet or thread to X via NyxID proxy (preferred) or direct API (fallback).
| name | broadcast-enrich-metrics |
| description | Join raw platform metrics JSONL back to registry/manifest metadata and compute experiment scoring priors. |
Use this skill after broadcast-kit fetch-metrics has produced raw metrics JSONL and the user wants feedback records for learning loops, A/B tests, or topic selection.
state/<platform>/work/metrics/<account>/<date>.jsonl.publish-registry or one or more platform manifests so records can be attributed back to content metadata.schema_version: broadcast.feedback.v0.metrics object.scores only as priors, not as final business truth.--dry-run first to inspect match rate before writing output.broadcast-kit enrich-metrics \
--metrics <raw-metrics.jsonl> \
--registry <publish_registry.json> \
--manifest <optional-manifest.yaml> \
--output <feedback_enriched.jsonl> \
--dry-run
Remove --dry-run to write the enriched JSONL.