Agent skill · software engineering · jeremylongshore
runway-performance-tuning
Analyze and improve Runway submission, queue, generation, download, and storage latency without unsafe polling or duplicate tasks. Use when an integration is slow. Trigger with: "speed up Runway", "Runway latency", "tune Runway performance".
Why this skill is useful
Provides specific implementation patterns and error handling for the Runway API that the AI wouldn't reliably generate on its own.
What it needs
Requires pip:runwayml installed locally. Requires runwayml account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Runway Queue-to-Asset Performance Tuning Overview End-to-end latency is a sequence of distinct phases: local admission, upload, provider queue, generation, output download, and owned storage. Optimize the measured bottleneck while preserving model quality, moderation, quota, and cost constraints. Prerequisites An SLO with percentile, modality, model, duration, and quality dimensions Traceable operation and task state timestamps Current model, input, tier, and pricing evidence Instructions Step 1: Instrument the phases Capture operation accepted, local queue start/end, upload start/end, provider create, each state transition, terminal state, download, validation, and storage completion. Use redacted IDs to join traces. Step 2: Separate queue from generation Report THROTTLED and PENDING residence independently from RUNNING. A concurrency bottleneck should not be misdiagnosed as model execution slowness. Step 3: Reduce input overhead Prefer already hosted HTTPS media or reusable ephemeral uploads when appropriate. Avoid large data URIs, validate formats before submission, and review silent auto-crop work. Step 4: Tune observation Use SDK wait helpers or polling at five seconds or more with jitter and backoff. Replace per-request busy loops with a bounded worker scheduler; more polls do not make generation finish sooner. Step 5: Evaluate routing and models Compare only eligible models or approved router policies on latency, quality, and credits. Use router dry runs for selection evidence and controlled canaries for realized performance. Step 6: Protect tail latency Apply deadlines, queue priorities, cancellation policy, circuit breaking for transient outages, and owned-output download retries. Never create duplicate generations as a latency hedge without explicit cost approval. Authentication Performance traces use server-side Runway access and must redact keys, prompt/media content, and signed URLs. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/runway-performance-tuning--51dff0