Agent skill

Assemblyai Reference Architecture

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

Analyze and design an AssemblyAI architecture spanning pre-recorded jobs, Streaming v3, LLM Gateway, callbacks, queues, retention, and audit evidence.

MITAuto-check passedAI & LLM Engineering

Install Assemblyai Reference Architecture

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

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

GitHub CLI
$ gh skill install jeremylongshore/tons-of-skills-marketplace assemblyai-reference-architecture --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-reference-architecture .claude/skills/assemblyai-reference-architecture && 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-reference-architecture
GitHub stars
2.8k
Token cost
~1.1k tokens
SKILL.md length
495 words
Files
2 (incl. references)
Skills in repo
3,342
Repo updated
First seen
Licence
MIT

At a glance

Analyze and design an AssemblyAI architecture spanning pre-recorded jobs, Streaming v3, LLM Gateway, callbacks, queues, retention, and audit evidence.

  • Works in 6 steps: Capture use cases, SLOs, languages, data… → Separate audio ingress, submitter, v3… → Assign each edge a principal,… → …
  • Performing system design
  • SKILL.md covers Overview, Prerequisites, Current Contract and Authentication, plus 8 more sections
  • Needs ASSEMBLYAI_API_KEY

What it does

Assemblyai Reference Architecture is an agent skill from jeremylongshore/tons-of-skills-marketplace. Analyze and design an AssemblyAI architecture spanning pre-recorded jobs, Streaming v3, LLM Gateway, callbacks, queues, retention, and audit evidence. Use when performing system design or review. Trigger with "AssemblyAI architecture" or "design AssemblyAI pipeline".

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

It sits in AI & LLM Engineering, covering Model routing and gateways and SOC 2 and security compliance. 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

  • Performing system design
  • With AssemblyAI architecture
  • Design AssemblyAI pipeline

Example prompts

  • “AssemblyAI architecture”
  • “design AssemblyAI pipeline”
  • “/assemblyai-reference-architecture”

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. Capture use cases, SLOs, languages, data classes, consent, region, retention, and cost.
  2. Separate audio ingress, submitter, v3 gateway, token issuer, callback ingress, queues, workers, and stores.
  3. Assign each edge a principal, credential, host, timeout, retry budget, and schema.
  4. Model job and session states including duplicates, reconnect, failure, and termination.
  5. Place LLM Gateway behind prompt allowlists and output schemas.
  6. Map deletion through vendor, storage, databases, caches, search, and analytics.

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 Reference Architecture loads about 1.1k tokens when it runs, and up to ~1.5k if it reads all its reference files. Until then it costs about 75 tokens; SKILL.md has 495 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~75
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
~1.5k

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). 495 words, ~1,110 tokens.

Download SKILL.mdSave it as .claude/skills/assemblyai-reference-architecture/SKILL.md (or your agent's skills folder). This skill also uses 1 other file; get the full folder from GitHub.
name
assemblyai-reference-architecture
description
Analyze and design an AssemblyAI architecture spanning pre-recorded jobs, Streaming v3, LLM Gateway, callbacks, queues, retention, and audit evidence. Use when performing system design or review. Trigger with "AssemblyAI architecture" or "design AssemblyAI pipeline".
allowed-tools
Read, Glob, Grep, Write, Edit
compatibility
Designed for Claude Code; live AssemblyAI work requires network access
argument-hint
<use-case> <region> <data-class>
version
1.12.0
license
MIT
author
Jeremy Longshore <jeremy@intentsolutions.io>
tags
saas, assemblyai
model
inherit
effort
high

AssemblyAI Governed Reference Architecture

Overview

Design explicit trust and lifecycle boundaries for ingestion, jobs, live turns, analysis, and deletion. Keep data, credentials, region, spend, and destructive state visible.

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 jobs are asynchronous resources addressed by transcript ID. Streaming v3 is a stateful billed session requiring termination. LLM Gateway is a separate analysis plane replacing LeMUR. Callback payloads differ by family. Region, principal, credential, retention, and deletion remain visible on every edge.

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. Capture use cases, SLOs, languages, data classes, consent, region, retention, and cost.
  2. Separate audio ingress, submitter, v3 gateway, token issuer, callback ingress, queues, workers, and stores.
  3. Assign each edge a principal, credential, host, timeout, retry budget, and schema.
  4. Model job and session states including duplicates, reconnect, failure, and termination.
  5. Place LLM Gateway behind prompt allowlists and output schemas.
  6. Map deletion through vendor, storage, databases, caches, search, and analytics.

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 (207 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

  • One opaque method cannot safely hide REST jobs and streaming sessions.
  • Polling in request handlers couples scaling and timeouts.
  • A design without credential, failure, rollback, and deletion paths is incomplete.

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-reference-architecture of jeremylongshore/tons-of-skills-marketplace.

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

Open the folder on GitHubat commit cfae287

Compare with similar skills

Assemblyai Reference Architecture 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 Reference Architecture compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Assemblyai Reference Architecture this skilljeremylongshore/tons-of-skills-marketplace2.8k—~1.1kAutomated safety check: PassMIT
Codememory Mark Constraintharrylettering/CodeMemory158—~793Automated safety check: PassNone
Shogun Bloom Configyohey-w/multi-agent-shogun1.4k—~3.1kAutomated safety check: PassMIT
Codemie Analyticscodemie-ai/codemie-code294—~7.5kAutomated safety check: PassApache-2.0
Model Routernidhi-singh02/agent-router112—~1.2kAutomated safety check: PassMIT
Codex Model Routing Teamzjp1997720/codex-model-routing-team158—~736Automated safety check: PassMIT

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Questions about Assemblyai Reference Architecture

What does Assemblyai Reference Architecture do?

Analyze and design an AssemblyAI architecture spanning pre-recorded jobs, Streaming v3, LLM Gateway, callbacks, queues, retention, and audit evidence. Assemblyai Reference Architecture is an agent skill from jeremylongshore/tons-of-skills-marketplace. Analyze and design an AssemblyAI architecture spanning pre-recorded jobs, Streaming v3, LLM Gateway, callbacks, queues, retention, and audit evidence.

When should I use Assemblyai Reference Architecture?

Assemblyai Reference Architecture fits situations like: performing system design; with AssemblyAI architecture; design AssemblyAI pipeline.

How do I install Assemblyai Reference Architecture in Claude Code?

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

How do I install Assemblyai Reference Architecture in Codex?

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

Can I use Assemblyai Reference Architecture 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-reference-architecture -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-reference-architecture, .gemini/skills/assemblyai-reference-architecture, .github/skills/assemblyai-reference-architecture and .opencode/skills/assemblyai-reference-architecture in your project.

What does Assemblyai Reference Architecture need to run?

Going by SKILL.md and its folder, Assemblyai Reference Architecture 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 Reference Architecture 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 Reference Architecture 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 Reference Architecture use?

Assemblyai Reference Architecture 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 Reference Architecture use?

About 1.1k tokens (SKILL.md is roughly 4.4k 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 Reference Architecture?

Skills that share tags, products or a category with Assemblyai Reference Architecture: Codememory Mark Constraint (harrylettering/CodeMemory, 158 stars), Shogun Bloom Config (yohey-w/multi-agent-shogun, 1.4k stars), Codemie Analytics (codemie-ai/codemie-code, 294 stars) and Model Router (nidhi-singh02/agent-router, 112 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Assemblyai Reference Architecture?

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.