FrancyJGLisboa

Create cross-platform agent skills from workflow descriptions. Activates when users ask to create an agent, automate a repetitive workflow, create a custom skill, or need advanced agent creation. Triggers on phrases like create agent for, automate workflow, create skill for, every day I have to, daily I need to, turn process into agent, need to automate, create a cross-platform skill, validate this skill, export this skill, migrate this skill. Supports single skills, multi-agent suites, transcript processing, template-based creation, interactive configuration, cross-platform export, and spec validation.

Summarizes open pull requests into a blockers-first standup digest. Activates when the user asks to summarize open PRs, find blocked pull requests, generate a PR standup, or triage review backlog from a PR export.

Provides comprehensive technical analysis for stocks and ETFs using RSI, MACD, Bollinger Bands, and other indicators. Activates when user requests stock analysis, technical indicators, trading signals, or market data for specific ticker symbols.

Cleans a weekly CRM export and produces a regional sales summary. Activates when the user asks to clean a CRM export, deduplicate sales rows, calculate regional totals, or generate a weekly sales report from a CSV.

Distill long AI-human sessions into inspectable reasoning models. Activates when users ask to extract the logic from this session, what were the assumptions, summarize the decisions, show the reasoning chain, session retrospective, extract formulas from conversation, what did we decide, assumption ledger, decision trajectory, reasoning graph, ambiguity check, session distillation, logic skeleton, dependency map, session shadow model. Triggers on phrases like what was the reasoning behind this session, extract assumptions from our conversation, map the decisions we made, show me the logic chain, what depends on what, find contradictions in this session, distill this conversation, compress this session, audit this reasoning, trace the decision path, cognitive audit.

Generate hand-solvable canonical math examples for any AI-built model, algorithm, or analytical pipeline. Activates when users ask to explain the math, show me the equations, create a canonical example, hand calculation, toy model, whiteboard example, validate the math, prove the formula, show intermediate steps, math unit test, sanity check, expected output, shadow model, or interpretability artifact. Triggers on phrases like show me the math behind this, create a hand-solvable example, extract the formulas, build a toy dataset, what are the equations, walk me through the calculation, produce a whiteboard version, map this to a simple example, math transparency, human readable math, algorithm decomposition, formula extraction.

Analyse a codebase to determine which of the four AI product value modes it embodies — Amplifier, Substitute, Job Creator, or Democratiser — and produce a sober, evidence-grounded verdict report in plain prose (Unicode text only, no emojis). Use this skill when the user wants to understand the strategic positioning or business model of an AI product by reading its code: triggers include "what mode is this", "detect AI value mode", "which quadrant does this fall into", "classify my AI product", or any pairing of a codebase path or pasted code with a question about how the product creates value, who its buyer is, or how it should be positioned. Trigger even when the user does not name the four modes explicitly — intent to classify an AI product from its code is sufficient. When asked for a diagram or infographic version, also renders the verdict as a self-contained HTML poster.

Generate ideas via named methods from creative practice.