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julianleopold
Profil créateur GitHub

julianleopold

Vue par dépôt de 5 skills collectés dans 1 dépôts GitHub.

skills collectés
5
dépôts
1
mis à jour
2026-04-22
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Principaux dépôts par nombre de skills collectés, avec leur part dans ce catalogue créateur et leur couverture métier.

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Dépôts et skills représentatifs

diagnose
Cuisiniers de restaurant

Diagnose espresso extraction issues by correlating machine telemetry with taste feedback. Use when user says: "what went wrong", "analyze that shot", "why did it taste [sour/bitter/flat]", "my shots are inconsistent", or asks about pressure spikes, flow issues, or extraction problems. Fetches shot data via analyze_shot MCP tool, interprets patterns, and provides actionable recommendations.

2026-04-22
feedback
Cuisiniers de restaurant

Gather shot feedback, analyze extraction, recommend adjustments, and record results. Use when user says: "/feedback", "I just pulled a shot", "how was that", "it tasted [sour/bitter/flat/good]", provides a star rating, shares taste observations, or asks "what should I adjust" after a shot. Owns the full shot feedback loop: gathering, analysis, tasting notes, and drink format.

2026-02-25
gaggimate-profiles
Développeurs de logiciels

Create custom espresso extraction profiles for Gaggimate-equipped machines (Gaggia Classic Pro, Gaggia Classic Evo, Rancilio Silvia). Use when designing pressure profiles, flow profiles, blooming profiles, lever simulation profiles, or helping with espresso extraction settings and troubleshooting. Also use when the user mentions Gaggimate, espresso profiles, pressure profiling, or extraction parameters.

2026-02-23
knowledge-lookup
Cuisiniers de restaurant

Answer espresso knowledge questions from the authoritative knowledge files. Use when the user asks about: temperature, pressure, ratios, grind settings, freshness, extraction theory, puck prep, channeling, baskets, decaf, blends, milk steaming, drink specs, profiles, shot styles, or any espresso concept. Routes to the correct knowledge file and answers from its content rather than from memory or training data.

2026-02-23
new-coffee
Barmans

Research a new coffee bean and propose starting extraction parameters. Use when: (1) user shares a new bag of coffee (photo, name, or description), (2) user says "new beans", "dialing in a new coffee", (3) user asks "where should I start with this coffee". Accepts bag photos (extracts info via vision) or text descriptions. Researches origin, process, roast level via web search, then recommends temperature, grind, ratio, and profile.

2026-02-23
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