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Join raw platform metrics JSONL back to registry/manifest metadata and compute experiment scoring priors.
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
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.