agentleFS
JonassuhardJonassuhard/claude-code-soul/skills/audit-short-1v1/SKILL.md

audit-short-1v1

Skill1 starsChanged 5 months agoMITView on GitHub

Audit pré-publication YouTube d'un short {{GAME_PROJECT}} 1v1. Score viralité 0-100 + verdict GO/WARN/NO-GO + recommandations basées sur algo YouTube Shorts 2026 + forensic du channel {{YT_CHANNEL}} (5 métriques pondérées : durée 35%, iconic personas 30%, action density 20%, hook variance 15%, bonus winner overlay). Use when about to upload a 1v1 short, or when user asks "audit ce short" / "est-ce que cette vidéo va marcher" / "score viralité" pour un .mp4 1v1.

The file

Files
SKILL.md

Skill : audit-short-1v1

Audit pré-publication d'un short {{GAME_PROJECT}} format 1v1. Score 0-100 + verdict GO/WARN/NO-GO + recommandations actionnables.

Prérequis

cd ~/Desktop/battle-engine
source .venv/bin/activate
# Deps : cv2 (deja), imagehash, pytesseract (deja installés)
# Tesseract binary : /opt/homebrew/bin/tesseract (deja present)

Invoquer

cd ~/Desktop/battle-engine
source .venv/bin/activate
python3 pipeline/audit_cli.py --preset 1v1 /path/to/video.mp4
# Avec matchup explicite (optionnel, sinon parsé du nom de fichier) :
python3 pipeline/audit_cli.py --preset 1v1 /path/to/video.mp4 --matchup mario,pikachu

Exit code : 0 si GO ou WARN, 1 si NO-GO.

Métriques et poids

MétriquePoidsPASSWARNFAIL
duration_s35%25-45s18-24s ou 46-60s<18s ou >60s
iconic_score30%≥2 icônes1 icône0 icône
action_density20%≥148-13<8
hook_variance_t215%≤734735-1200>1200

Icônes : Mario, Pikachu, Sonic, Goku, Steve (Minecraft).

Bonus : +5 pts si overlay winner détecté (OCR sur les 5 dernières frames).

Hard gates NO-GO : résolution != 1080x1920, black_frame_ratio > 10%, freeze_ratio > 15%, durée > 90s.

Interpréter le score

ScoreVerdictAction
60-100GO — top tier probableUploader
40-59WARN — mid tierEnvisager re-render ou uploader quand même
0-39NO-GO — sous-performance attendueRe-render avec autre seed ou changer matchup

Floor 55 : si une métrique est critique (FAIL avec poids élevé), le score est capé à 55 même si les autres sont PASS.

Que faire si NO-GO

  1. duration_s FAIL (>60s) : Re-render avec autre seed. Réduire HP de 20% pour finish plus rapide.
  2. iconic_score FAIL (0) : Remplacer 1 perso par Mario/Pikachu/Sonic/Goku/Steve. +67% vues en moyenne sur le channel.
  3. action_density FAIL (<8) : Combat statique. Vérifier hitboxes ou augmenter agressivité IA. Re-render.
  4. hook_variance_t2 FAIL (>1200) : Intro corrompue ou bug de spawn à t=1.5s. Re-render impératif.
  5. freeze_ratio FAIL : Frames figées. Bug Godot probable. Re-render.

Exemple output JSON

{
  "score": 100,
  "verdict": "GO — top tier probable",
  "preset": "1v1",
  "hard_gate": null,
  "floor_triggered": false,
  "metrics": {
    "duration_s": 35.57,
    "resolution": "1080x1920",
    "hook_variance_t2": 0.0,
    "action_density": 20.57,
    "black_frame_ratio": 0.0,
    "freeze_ratio": 0.0,
    "winner_text_present": true,
    "multi_fighter_visible_t2": 5,
    "iconic_score": 2,
    "matchup": ["mario", "pikachu"]
  },
  "contributions": {
    "duration_s": {"value": 35.57, "verdict": "PASS", "contribution": 35.0},
    "iconic_score": {"value": 2.0, "verdict": "PASS", "contribution": 30.0},
    "action_density": {"value": 20.57, "verdict": "PASS", "contribution": 20.0},
    "hook_variance_t2": {"value": 0.0, "verdict": "PASS", "contribution": 15.0}
  },
  "bonus": {"winner_overlay": "+5"},
  "recommendations": []
}

Calibration (24/05/2026)

Calibré sur 111 vidéos {{YT_CHANNEL}}.

  • Seuils forensic (Pearson) : hook_variance -0.734, duration -0.513, action_density +0.184, iconic +0.264.
  • Sweet spot duration 1v1 : 27-35s (batch 18-20 successful).
  • Personages iconiques both = avg 723 views, none = 477 views.

OUTPUT CONTRACT

Respecte ~/.claude/rules/output-contract.md.

Attendu : JSON output stdout (format exemple ci-dessus) + exit code 0/1 selon verdict

Checks :

  • JSON sortie parseable : python3 -c "import json,sys; json.loads(sys.stdin.read())" ≤ exit 0
  • Champs obligatoires : score, verdict, preset, metrics, contributions, recommendations
  • score ∈ [0, 100]
  • verdict ∈ {"GO — top tier probable", "WARN — mid tier", "NO-GO — sous-performance attendue, refaire"}
  • Exit code 0 si score ≥ 40, exit 1 si < 40
  • Si NO-GO : recommendations non vide avec action concrète par métrique FAIL
  • Hard gates checkés (résolution, freeze, black, durée)

Format réponse : LIVRABLE: audit 1v1 / SCORE: X / VERDICT: GO|WARN|NO-GO / METRICS: dur=A iconic=B action=C var=D / RECO: <liste si NO-GO> / NEXT: <upload | re-render seed Y | changer matchup>

Anti-hallucination : Si le script Python a échoué : INCOMPLETE: audit_cli.py failed (<erreur>). Si la vidéo n'est pas 1080×1920 : hard gate NO-GO immédiat.

Download now (ZIP)

Does it work?

Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.

No reviews yet

People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.

  • It worked
  • Partly
  • It didn't
What did you use it for? e.g. Reviewing pull requests in a Rails app

Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.

Your trail

Files you open will collect here, so you can find them again.

Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.

Now do this for your own.

Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.