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jbaruch/speaker-toolkit

Five-skill presentation system: ingest talks into a rhetoric vault, run interactive clarification, generate a speaker profile, create presentations that match your documented patterns, and produce the deck illustrations + thumbnail visual layer. Includes a 102-entry Presentation Patterns taxonomy (91 observable, 11 unobservable go-live items) for scoring, brainstorming, and go-live preparation.

93

1.43x
Quality

94%

Does it follow best practices?

Impact

93%

1.43x

Average score across 21 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

Overview
Quality
Evals
Security
Files

task.mdevals/scenario-7/

Humor Post-Mortem and Blind Spot Debrief

Problem/Feature Description

Two talks have been processed through vault-ingress and their analysis is complete. Now the speaker needs a post-analysis debrief covering:

  1. Humor post-mortem — walk through each identified humor beat and grade its effectiveness
  2. Blind spot capture — probe for information transcripts cannot reveal (audience reactions, stage moments, room context)
  3. Recency adaptation — the recent talk gets detailed per-joke questioning; the old talk gets compressed broad-strokes questions

Setup

Download the two fixed analysis files:

curl -sLO https://github.com/jbaruch/speaker-toolkit/raw/main/eval-resources/humor-postmortem-blind-spots/test_analysis_recent.json
curl -sLO https://github.com/jbaruch/speaker-toolkit/raw/main/eval-resources/humor-postmortem-blind-spots/test_analysis_old.json

Task

Process both talk analyses and produce structured debrief outputs:

  1. For the recent talk (test_analysis_recent.json — "Robocoders: Judgment Day", 7 days ago):

    • Generate a debrief questionnaire that walks the speaker through the recent talk's humor performance
    • Include questions about each meme slide's audience reaction
    • Cover the demo sections (d1, d2) and the theatrical opening (bs3)
  2. For the old talk (test_analysis_old.json — "Groovy Puzzlers", 3 years ago):

    • Generate a debrief appropriate to a talk delivered 3 years ago
    • Still capture notable audience moments
  3. Produce structured output as JSON files:

    • debrief_questionnaire_recent.json — the questionnaire for the recent talk
    • debrief_questionnaire_old.json — the questionnaire for the old talk
    • Each question should reference specific analysis observations (humor beat IDs, slide numbers, quotes)
    • Blind spot observations stored as structured fields, not free text

evals

README.md

tile.json