fpf-problem-solving

fpf-problem-solving is a Structured reasoning & decision frameworks skill for AI agents, published by CodeAlive-AI in the ai-driven-development repository on GitHub. Skillspace rates fpf-problem-solving C (77/100) and it passed the safety scan; the rating is based on static analysis only.

First Principles Framework (FPF) — thinking amplifier. Use when user wants to think through a complex problem, architect a system, evaluate alternatives, decompose complexity, classify problems, define quality attributes, plan rigorously, apply an FPF pattern to a first useful result, decide under uncertainty, establish causality, reason about time and trends, describe or synthesize architecture, check mathematical model fit, govern ontic/U-kind introduction, publish multi-view artifacts, refresh SoTA packs, trace provenance, or improve pattern quality. Also triggers on: FPF, bounded contexts, SoTA packs, assurance calculus, decision theory, causal reasoning, temporal reasoning, architecture description, modularity, constraint-governed unfolding, narrative rendering, structural adequacy, cultural evolution, quality gates, lexical discipline, FPF Parts A-I. Not for simple task planning, general philosophy, or Agile unrelated to FPF.

Grade

C

Quality

77 / 100

Safety

Passed

GitHub stars

100

Unproven: rated by static analysis only, not yet compared head-to-head.

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