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Agent skill

Assemblyai Performance Tuning

by jeremylongshore in jeremylongshore/tons-of-skills-marketplace

Analyze and tune AssemblyAI model choice, audio delivery, polling, Streaming v3 turns, concurrency, and downstream work.

MITAuto-check passed

Install Assemblyai Performance Tuning

skills CLI
$ npx skills add jeremylongshore/tons-of-skills-marketplace --skill assemblyai-performance-tuning -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace assemblyai-performance-tuning --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jeremylongshore/tons-of-skills-marketplace.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/.curated/assemblyai-performance-tuning .claude/skills/assemblyai-performance-tuning && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
assemblyai-performance-tuning
GitHub stars
2.8k
Token cost
~1.1k tokens
SKILL.md length
469 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Analyze and tune AssemblyAI model choice, audio delivery, polling, Streaming v3 turns, concurrency, and downstream work.

  • Works in 6 steps: Define queue, completion, first-turn,… → Build a representative synthetic or… → Benchmark current supported models and… → …
  • Pursuing measured latency
  • SKILL.md covers Overview, Prerequisites, Current Contract and Authentication, plus 8 more sections
  • Needs ASSEMBLYAI_API_KEY

What it does

Assemblyai Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. 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".

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 2 other files, including reference files (for example `references/official-docs.md`). Compatibility notes: Designed for Claude Code; live AssemblyAI work requires network access

The repository describes itself as: Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com. The licence is MIT.

When your agent uses it

  • Pursuing measured latency
  • Throughput goals
  • With tune AssemblyAI
  • AssemblyAI latency

Example prompts

  • “tune AssemblyAI”
  • “AssemblyAI latency”
  • “/assemblyai-performance-tuning”

Requirements

  • A credential in ASSEMBLYAI_API_KEY
  • Compatibility (from SKILL.md): Designed for Claude Code; live AssemblyAI work requires network access
  • Pre-approved tools (allowed-tools): Read, Glob, Grep, Write, Edit

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  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.

What it can do on your machine

Read from SKILL.md and the folder at commit cfae287. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Glob
    • Grep
    • Write
    • Edit

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • ASSEMBLYAI_API_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

  • Compatibility

    Designed for Claude Code; live AssemblyAI work requires network access

    From compatibility in the SKILL.md frontmatter.

Context cost

Assemblyai Performance Tuning loads about 1.1k tokens when it runs, and up to ~1.4k if it reads all its reference files. Until then it costs about 66 tokens; SKILL.md has 469 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~66
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~1.4k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jeremylongshore/tons-of-skills-marketplace at commit cfae287, republished under its MIT licence (© jeremylongshore). 469 words, ~1,063 tokens.

Download SKILL.mdSave it as .claude/skills/assemblyai-performance-tuning/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
assemblyai-performance-tuning
description
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".
allowed-tools
Read, Glob, Grep, Write, Edit
compatibility
Designed for Claude Code; live AssemblyAI work requires network access
argument-hint
<workload-profile> <service-level-objective>
version
1.12.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, assemblyai
model
inherit
effort
high

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 ASSEMBLYAI_API_KEY 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.

Show full SKILL.md (203 more words)Show less

Approval Boundaries

Require an accountable owner before live audio processing, production credential or endpoint changes, paid model or capacity changes, content retention, callback replay, deployment, or deletion. Read-only repository inspection and synthetic offline validation do not authorize live vendor actions.

Failure Modes

  • Faster output with unacceptable accuracy is a regression.
  • Audio preprocessing can introduce harmful artifacts.
  • Lower latency with more retries or abandoned sessions is not an improvement.

Output

Return the operation scope, environment, region, contract surface, authorization class, model and feature decisions, deterministic validation results, content-free identifiers, risks, cleanup or rollback state, and a concise pass/fail receipt. Exclude credentials, signed URLs, audio, transcript text, prompts, and customer-derived content.

Example

  • Start with the named environment, approved regional host, synthetic fixture identity, and bounded operation budget.
  • Finish with safe IDs, contract and assertion counts, terminal state, cleanup status, and the decision owner; never reproduce speech content.

Validation

Rerun the smallest relevant deterministic check, compare actual state with the requested outcome and current first-party contract, verify sensitive fields are absent from evidence, and confirm rollback, termination, or deletion state before reporting success.

References

Review the dated first-party evidence map before relying on any model, parameter, limit, price, region, or lifecycle claim.

© jeremylongshore, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 1 other file (references) in skills/.curated/assemblyai-performance-tuning of jeremylongshore/tons-of-skills-marketplace.

  • SKILL.md
  • references/official-docs.md

Open the folder on GitHubat commit cfae287

Compare with similar skills

Assemblyai Performance Tuning next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Assemblyai Performance Tuning compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Assemblyai Performance Tuning this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: PassMIT
HyperFrames Audioheygen-com/hyperframes60k1 repos~6.5kAutomated safety check: PassApache-2.0
LLM Fine Tuningsickn33/agentic-awesome-skills47k1 repos~2.3kAutomated safety check: PassMIT
Audio Descriptionsthedaviddias/Front-End-Checklist74k—~549Automated safety check: PassMIT
Fine Tuning With TrlOrchestra-Research/AI-Research-SKILLs13k6 repos~2.9kAutomated safety check: PassMIT
Venice Audio Musicnexu-io/open-design100k—~297Automated safety check: PassApache-2.0

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Questions about Assemblyai Performance Tuning

What does Assemblyai Performance Tuning do?

Analyze and tune AssemblyAI model choice, audio delivery, polling, Streaming v3 turns, concurrency, and downstream work. Assemblyai Performance Tuning is an agent skill from jeremylongshore/tons-of-skills-marketplace. Analyze and tune AssemblyAI model choice, audio delivery, polling, Streaming v3 turns, concurrency, and downstream work.

When should I use Assemblyai Performance Tuning?

Assemblyai Performance Tuning fits situations like: pursuing measured latency; throughput goals; with tune AssemblyAI; assemblyAI latency.

How do I install Assemblyai Performance Tuning in Claude Code?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill assemblyai-performance-tuning -a claude-code`. Or copy the skill folder (skills/.curated/assemblyai-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .claude/skills/assemblyai-performance-tuning in your project. Claude Code loads it when a task matches its description.

How do I install Assemblyai Performance Tuning in Codex?

Run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill assemblyai-performance-tuning -a codex`. Or copy the skill folder (skills/.curated/assemblyai-performance-tuning in jeremylongshore/tons-of-skills-marketplace) into .agents/skills/assemblyai-performance-tuning in your project. Codex loads it when a task matches its description.

Can I use Assemblyai Performance Tuning in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jeremylongshore/tons-of-skills-marketplace --skill assemblyai-performance-tuning -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/assemblyai-performance-tuning, .gemini/skills/assemblyai-performance-tuning, .github/skills/assemblyai-performance-tuning and .opencode/skills/assemblyai-performance-tuning in your project.

What does Assemblyai Performance Tuning need to run?

Going by SKILL.md and its folder, Assemblyai Performance Tuning needs credentials named ASSEMBLYAI_API_KEY. Our summary lists: A credential in ASSEMBLYAI_API_KEY. Its frontmatter pre-approves these tools: Read, Glob, Grep, Write, Edit. Compatibility (from SKILL.md): Designed for Claude Code; live AssemblyAI work requires network access.

Does Assemblyai Performance Tuning access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Assemblyai Performance Tuning safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Assemblyai Performance Tuning use?

Assemblyai Performance Tuning is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Assemblyai Performance Tuning use?

About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 347 tokens, read only when the agent opens those files.

What are the alternatives to Assemblyai Performance Tuning?

Skills that share tags, products or a category with Assemblyai Performance Tuning: HyperFrames Audio (heygen-com/hyperframes, 60k stars), LLM Fine Tuning (sickn33/agentic-awesome-skills, 47k stars), Audio Descriptions (thedaviddias/Front-End-Checklist, 74k stars) and Fine Tuning With Trl (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Assemblyai Performance Tuning?

jeremylongshore (a GitHub user) maintains it in jeremylongshore/tons-of-skills-marketplace, which has 2,827 GitHub stars. The repository holds 3,342 skills in this directory. The repository was last updated on October 10, 2026.

Source: jeremylongshore/tons-of-skills-marketplace on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.