ember-memory-test/episodes/TRAZA_r46seccion2l1-prisma-viz-aplicado-anlis_S20260524.R39_XX.ops.2.hot_inf.in.cc.es.000.MGQ_J.PMCFK_E.SGNFD.md
Ember 10765e7acc feat(episode): TRAZA_r46seccion2l1-prisma-viz-aplicado-anlis_S20260524.R39_XX.ops.2.hot_inf.in.cc.es.000.MGQ_J.PMCFK_E.SGNFD
Skill: NONE | Type: troubleshooting
Summary: EPISODIO 39 — ember_experience: [R46.seccion2.L1] PRISMA-VIZ aplicado — Análisis
2026-05-26 01:01:25 +00:00

3.7 KiB
Raw Blame History

episode_id puente_flat session_code acto_dialogico actor_flujo criticidad_aegis skill_dominante fase_proyecto tipo_semantico summary_one_line source_type trust_boundary created_at relectura_tagged forgejo_commit_sha
cd4ff6e5-fccd-4b5d-8183-da12a8dde1e4 TRAZA_r46seccion2l1-prisma-viz-aplicado-anlis_S20260524.R39_XX.ops.2.hot_inf.in.cc.es.000.MGQ_J.PMCFK_E.SGNFD S20260524.VERIFY_MARIMO_RENDER_BRASALUZ informar multi_actor low NONE operations troubleshooting EPISODIO 39 — ember_experience: [R46.seccion2.L1] PRISMA-VIZ aplicado — Análisis problema da claude_code internal 2026-05-26T01:01:02.418131+00:00 false pending

[R46.seccion2.L1] PRISMA-VIZ aplicado — Análisis problema dashboard monitoring pipeline memoria EMBER

Ejecuté PRISMA-VIZ Pipeline [0] Diagnose → [1] Classify → [2] Select method → [3] Generate → [4] Validate sobre tu problema R45+R46.

5 preguntas pre-generation PRISMA-VIZ (auto-respondidas)

# Pregunta Respuesta diagnóstica
1 STRUCTURE Branched + Causal + Comparative (27 estaciones + cross-store + bugs)
2 DIMENSIONS 3D+ (throughput × ratio retrieval × LEXICON × crisol × drift × bugs)
3 TYPE Multi-tipo: comparativo (5 propuestas) + exploratory (gaps HyDE unknown) + sequential (27 estaciones) + causal (root causes)
4 DETAIL LEVEL L2-L3 (HTML interactive o React component — John pidió "tiempo real + bombos y platillos")
5 QUANTIFIABLE SÍ alto (throughput counts, retrieval ratios, drift numbers) → Decision Matrix + Sankey + Flowchart

Top 5 métodos PRISMA-VIZ recomendados (matched ranking)

Rank Método Aplicación Justificación PRISMA-VIZ
🥇 1 Sankey Diagram (L2 HTML) 27 estaciones pipeline flow + volumen fragments "Quantitative flow + how it splits + resource distribution"
🥈 2 Flowchart (L2 HTML) Crisol F0-F6 + decision points cross-store "Process/workflow + pipeline + if/then"
🥉 3 Decision Matrix (L1 Mermaid) 5 propuestas dashboard ranking multi-criteria "Multi-criteria comparison + weight factors + scoring"
4 Graph of Thoughts (L2) Cross-store feedback loops + drift dependencies "Multiple variables + feedback loops + everything connected"
5 Fishbone (Ishikawa) (L1 Mermaid) Root cause bugs (B-NEW11 NULL + B-NEW26 manifest) "Why did it happen + root cause + diagnosis"

Guidance PRISMA-VIZ refina Propuesta R45

Aplicación concreta refinada de PRISMA-VIZ a las 5 propuestas R45:

Propuesta R45 Métodos PRISMA-VIZ óptimos aplicables
A. Notebook marimo LIVE Flowchart (state machine) + Sankey (volume flow) + Heatmap (cross-tab) + Timeline (24h history)
B. Tests HyDE Exhaustivos Decision Matrix (38 EPs × precision/recall/MRR) + Calibration plot (VIZ-PUBLICATION J family)
C. Dashboard SLI/SLO Decision Matrix (SLIs × SLOs × error budget) + Forest plot (meta-analysis) + Timeline trends
D. Sankey 27 estaciones Sankey PRISMA-VIZ (esto es el método PRIMARIO PRISMA-VIZ ranked #1)
E. Suite combinada TODOS los 5 métodos aplicados across notebooks + reportes

Skill DIRECTOR audiovisual (mencionado John "audiovisuales")

DIRECTOR skill (no leí completo R46) — declarado catálogo CLAUDE.md raíz: "AV production pipeline / produce video, comercial". Esto sugiere DIRECTOR podría fabricar video tutorial corto explicando pipeline EMBER. Pero ese skill es heavy (~5-15K tokens + production tools).

Recomendación PRISMA-VIZ + R45 actualizada: