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fiber-scheduling-theory skill

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This skill analyzes Fiber scheduling theory to optimize rendering priorities, prevent preemption issues, and avoid starvation in multi-lane UI updates.

npx playbooks add skill harborgrid-justin/lexiflow-premium --skill fiber-scheduling-theory

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SKILL.md
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---
name: fiber-scheduling-theory
description: Apply deep knowledge of Fiber scheduling to reason about rendering priorities, preemption, and starvation avoidance.
---

# Fiber Scheduling Theory (React 18)

## Summary

Apply deep knowledge of Fiber scheduling to reason about rendering priorities, preemption, and starvation avoidance.

## Key Capabilities

- Interpret scheduler lanes and priority escalation behavior.
- Model preemption effects on UI atomicity guarantees.
- Diagnose starvation risks and mitigate via boundary design.

## PhD-Level Challenges

- Construct a formal scheduling model for multi-lane updates.
- Derive starvation bounds under adversarial update patterns.
- Evaluate performance regressions using synthetic lane stress tests.

## Acceptance Criteria

- Present a lane diagram for a complex interaction scenario.
- Validate that high-priority input stays responsive under load.
- Explain trade-offs in at least two real scheduling decisions.

Overview

This skill applies deep knowledge of React Fiber scheduling to reason about rendering priorities, preemption, and starvation avoidance. It focuses on interpreting scheduler lanes, modeling preemption effects on UI atomicity, and designing boundaries that prevent starvation while preserving responsiveness. The skill is geared toward engineers building responsive, concurrent UIs and researchers formalizing scheduler behavior.

How this skill works

The skill inspects lane assignments, priority escalation, and lane merging rules to produce diagrams and step-by-step traces of update lifecycles. It models preemption by simulating interrupted work, capturing what is committed versus abandoned and showing how atomicity guarantees can be violated or maintained. It also evaluates starvation risks by generating adversarial update patterns and proposing boundary or throttling mitigations.

When to use it

  • Designing complex interactions where multiple priorities (input, transitions, sync) compete
  • Diagnosing regressions in responsiveness under heavy background work
  • Evaluating whether UI atomicity is preserved across preemptible updates
  • Formal analysis or testing of scheduler behavior for performance guarantees
  • Creating stress tests that reproduce priority inversion or starvation

Best practices

  • Map user-facing events to explicit lanes and document intended escalation paths
  • Use clear boundaries (e.g., Suspense/fallbacks) to limit starvation domains
  • Prefer splitting long tasks and yielding to higher-priority lanes to keep input responsive
  • Measure with synthetic lane stress tests and validate high-priority latency under load
  • Explain trade-offs when disabling preemption vs. preserving atomic commits

Example use cases

  • Produce a lane diagram for a complex form with autosave, live validation, and hotspot input
  • Simulate preemption to demonstrate when a transition loses atomicity and recommend fixes
  • Derive worst-case starvation bounds for a feed that receives continuous low-priority updates
  • Create stress tests that confirm high-priority input remains responsive with background rendering
  • Compare two scheduling strategies and document throughput vs. responsiveness trade-offs

FAQ

Can this skill prove hard real-time guarantees for UI updates?

No. It provides formal models and bounds under realistic scheduler rules, but JavaScript and browser environments prevent hard real-time guarantees.

Will it change React behavior directly?

No. It analyzes and models scheduler behavior and suggests design or code changes you can apply; it does not modify the runtime scheduler.