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pi-fabric
pi-fabric には monotykamary から収集した 10 個の skills があり、リポジトリ単位の職業カバレッジとサイト内 skill 詳細ページを表示します。
このリポジトリの skills
Creates a custom persistent Pi Fabric supervisor or advisor. Use for ambient supervision, ongoing peer review, an advisor, or a goal watcher without another extension.
Runs a bounded multi-perspective Pi Fabric council with independent reviewers and optional synthesis. Use for architecture choices, plans, reviews, and adversarial cross-checking.
Multi-model deliberation. Up to 8 distinct models answer in parallel with web-capable tools, then a judge compares consensus, contradictions, coverage gaps, unique insights, and blind spots. Use when the cost of being wrong justifies multiple completions.
Recursively decomposes oversized tasks into bounded child Pi agents with fresh context windows. Use for whole-repo audits, massive-context analysis, and multi-file refactors that do not fit one context.
Uses Fabric's typed Schema evidence loop and, when enabled, its bounded local-file transaction channel. Use when surprise must void a plan and mutation claims need explicit postconditions.
Creates a self-organizing team of persistent Pi Fabric actors with durable topics, mailboxes, and compare-and-swap tasks. Use for messenger-like collaboration and long-lived delegated work.
Starts a persistent Pi Fabric peer advisor that reviews the main agent at decision points and surfaces only concrete, material advice. Use for ambient correctness review without another extension.
Reference for `fabric_exec` TypeScript programs: Pi core tool signatures, discovery, provider and MCP proxies, named strings, return shapes, and schema-driven error recovery. Load before the first Fabric call or after an argument-shape error.
Starts a persistent Pi Fabric supervisor that watches the main session toward a concrete goal and steers only when needed. Use for long-running goal supervision without another extension.
Runs a dynamic Pi Fabric workflow with code-held phases, fan-out, pipelines, structured agents, and synthesis. Use for large audits, migrations, parallel research, or explicit workflow requests.