turbocharge

Original：🇺🇸 English

Translated

Use when the user wants to push past conventional workflow limits with advanced performance techniques like parallel orchestration, streaming pipelines, or adaptive routing.

2installs

Sourcesharpdeveye/maestro

Added on2026-04-11

NPX Install

npx skill4agent add sharpdeveye/maestro turbocharge

SKILL.md Content

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MANDATORY PREPARATION

Invoke {{command_prefix}}agent-workflow — it contains workflow principles, anti-patterns, and the Context Gathering Protocol. Follow the protocol before proceeding — if no workflow context exists yet, you MUST run {{command_prefix}}teach-maestro first.

Start your response with:

text

──────────── ⚡ TURBOCHARGE ─────────────
》》》 Entering turbocharge mode...

Push a workflow past conventional limits. This isn't about adding features — it's about making existing capabilities operate at a level users didn't think was possible.

EXTRA IMPORTANT: Context determines what "extraordinary" means. Understand the project's scale before deciding what to turbocharge.

Propose Before Building

Think through 2-3 different directions with trade-offs
Present these options to the user and wait for their selection before writing code
Only proceed with the confirmed direction

For high-throughput workflows

Parallel fan-out: Split input, process N simultaneously, merge results
Streaming pipelines: Start processing step N+1 while step N runs
Progressive quality: Fast pass on everything, detailed pass on flagged items
Smart batching: Group similar items, outliers get individual treatment

For latency-critical workflows

Speculative execution: Start likely next step before current finishes
Cached warm paths: Pre-compute responses for common patterns
Model cascading: Try fastest model first, escalate only when needed

For reliability-critical workflows

Automatic failover: Detect failures, switch to alternatives automatically
State checkpointing: Save state, resume from any point after crash
Chaos testing: Intentionally break dependencies to verify recovery

For adaptive workflows

Complexity routing: Route simple inputs to fast paths, complex to thorough
Dynamic model selection: Choose model based on task requirements
Feedback-driven optimization: Track what works best, adapt routing

Progressive enhancement is non-negotiable

Every turbocharge technique must degrade gracefully. The workflow without the enhancement must still work.

Verification

Performance test: Is it measurably faster/cheaper/more reliable?
Degradation test: Disable enhancement — does it still work?
Cost test: Does improvement justify complexity?
Maintenance test: Can someone else maintain this in 6 months?

Recommended Next Step

After turbocharging, run

{{command_prefix}}evaluate

to verify the enhancement works and degrades gracefully.

NEVER:

Turbocharge before the workflow is correct (make it right, then make it fast)
Add complexity without measuring the improvement
Build self-healing without testing the healing
Layer multiple turbocharge techniques at once