Agent skill · marketing growth · jeremylongshore
assemblyai-performance-tuning
Analyze and tune AssemblyAI model choice, audio delivery, polling, Streaming v3 turns, concurrency, and downstream work. Use when pursuing measured latency or throughput goals. Trigger with "tune AssemblyAI" or "AssemblyAI latency".
Why this skill is useful
Adds executable scripts for optimizing AssemblyAI API performance through caching, parallel processing, and model selection that aren't in public docs.
What it needs
Requires assemblyai, lru-cache, p-queue installed locally. Requires assemblyai account access. About 2k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
AssemblyAI Latency and Throughput Tuning Overview Tune latency and throughput with controlled, representative experiments. Preserve accuracy, privacy, credentials, spend, and rollback as separate gates. Prerequisites The target repository or integration path and the requested operator outcome. The AssemblyAI project, environment, region, data classification, and accountable owner. Current first-party documentation plus credentials only for a narrowly approved live check. Current Contract Pre-recorded and streaming optimize different outcomes. Current models differ in languages, accuracy, latency, prompting, endpointing, and price. Benchmark representative approved fixtures rather than inherited labels such as Best or Nano, and keep privacy, quality, and spend as co-equal gates. Authentication For live work, inject ASSEMBLYAIAPIKEY from an approved secret manager and send the raw value only in the AssemblyAI Authorization header to the configured first-party host. Never print, commit, place in a URL, or expose it to an untrusted client. Callback secrets and temporary streaming tokens are separate credentials. Instructions 1. Define queue, completion, first-turn, finalization, quality, and cost objectives. 2. Build a representative synthetic or approved evaluation set. 3. Benchmark current supported models and only required features. 4. Replace aggressive polling with callbacks and tune admission separately. 5. Verify audio format, pacing, turn settings, and termination for streaming. 6. Canary one change at a time and retain rollback thresholds. Tool Discipline Use Read, Glob, and Grep to inspect repository code, configuration, fixtures, and evidence. Use Write and Edit only for approved implementation or documentation changes. Do not call AssemblyAI, upload audio, open a streaming session, mint a token, replay a callback, deploy, rotate a key, or delete a transcript merely because this skill was invoked. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/assemblyai-performance-tuning