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Skill chaining is the architectural pattern of building modular AI pipelines — many small skills with shared modes, orchestrated through routing and quality gates — instead of one monolithic skill that tries to do everything. The principle was articulated in the 2026-02-26 mastermind through Lou’s walkthrough of how he re-architected the GEARS system from one big skill into three skills sharing common modes. The concept grew into a load-bearing hub with 16 inbound references and was split on 2026-05-22 into three sub-insights:
Sub-Insights
- Insight - Skill Composition — Many Small Skills With Shared Modes Beat One Big Monolith — the architectural case. Why modularity wins: separation of concerns, composability through shared resources, communication via structured objects, the folder as the deliverable. The principles that justify the pattern.
- Insight - Skill Orchestration — Forking, Quality Gates, and Pipeline Mechanics Make Chains Actually Run — the operational mechanics. The five techniques that make composed chains work: context isolation via forking, quality validation at handoffs, configuration-as-text, parallel work-trees, and conversation as the interface. The how-to-run-it layer.
- Insight - Skill Scoping — Not Every Prompt Wants to Be a Skill, and Not Every Skill Wants to Grow — the discipline of restraint. The hardest call in a skill-based system is often not building the next skill. Skill slop, scope evaluation, model routing, form-factor discipline (CLI-first). The prerequisite question that the other two sub-insights assume already answered.
Read all three for the full picture. Each stands on its own; together they describe what it means to build and maintain a skill-based AI system without it collapsing into orchestration chaos.
Original Insight Quote
“Instead of having one big monolith skill, now Gears is actually 3 skills. One is the initialization phase, gears onboard is the skill that creates the schema, and gears content is another skill that actually generates the hub… This used to be one skill that called all of these things separately. Now there are three skills that, instead of calling another skill, what it calls is these things called modes. And modes are essentially like skills, except they’re not skills. They don’t have the front matter that makes them skills… In the interest of progressive disclosure, you want to make sure that when you’re loading the skill, you’re not loading a single file that has all of this stuff in it.” — Lou, 2026-02-26 Mastermind (the GEARS monolith-to-modular re-architecture)
Why This Was Split
The hub accumulated 16 inbound related-insights references — over the >15 hub-overload threshold defined in core-principles.md. The hub was doing three distinct jobs: making the architectural case for modularity, naming the operational mechanics of orchestration, and articulating the discipline of when to chain. Three theses bundled into one hub. The split lets each one stand on its own with fresh link capacity, and lets inbound insights point at the facet they actually lean on. Notably, the hub also had eviction history (Use Claude to Evaluate Whether a Project Should Become a Skill had been evicted during a prior cap-saturation event) — that eviction is reversed as part of this split, with the evicted insight reconnected to the Insight - Skill Scoping — Not Every Prompt Wants to Be a Skill, and Not Every Skill Wants to Grow sub-insight where it actually belongs. Executed via /mastermind-hub-split on 2026-05-22.