Agent skill

Output Dev LLM Streaming

Implement LLM text streaming in Output workflow steps with generateTextWithStreaming, Agent.generateWithStreaming, streamText, or Agent.stream.

Apache-2.0Auto-check passed

Install Output Dev LLM Streaming

skills CLI

$ npx skills add growthxai/output --skill output-dev-llm-streaming -a claude-code

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

GitHub CLI

$ gh skill install growthxai/output output-dev-llm-streaming --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/growthxai/output.git skills-src && mkdir -p .claude/skills && cp -r skills-src/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming .claude/skills/output-dev-llm-streaming && 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/

Paste into Claude Code

Install the "output-dev-llm-streaming" agent skill from https://github.com/growthxai/output/tree/main/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming into .claude/skills/output-dev-llm-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "output-dev-llm-streaming", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/growthxai/output/tree/main/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add growthxai/output --skill output-dev-llm-streaming -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install growthxai/output output-dev-llm-streaming --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/growthxai/output.git skills-src && mkdir -p .agents/skills && cp -r skills-src/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming .agents/skills/output-dev-llm-streaming && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "output-dev-llm-streaming" agent skill from https://github.com/growthxai/output/tree/main/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming into .agents/skills/output-dev-llm-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "output-dev-llm-streaming", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add growthxai/output --skill output-dev-llm-streaming -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install growthxai/output output-dev-llm-streaming --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/growthxai/output.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming .cursor/skills/output-dev-llm-streaming && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "output-dev-llm-streaming" agent skill from https://github.com/growthxai/output/tree/main/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming into .cursor/skills/output-dev-llm-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "output-dev-llm-streaming", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/growthxai/output.git --path coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add growthxai/output --skill output-dev-llm-streaming -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install growthxai/output output-dev-llm-streaming --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/growthxai/output.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming .gemini/skills/output-dev-llm-streaming && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "output-dev-llm-streaming" agent skill from https://github.com/growthxai/output/tree/main/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming into .gemini/skills/output-dev-llm-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "output-dev-llm-streaming", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install growthxai/output output-dev-llm-streaming

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add growthxai/output --skill output-dev-llm-streaming -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/growthxai/output.git skills-src && mkdir -p .github/skills && cp -r skills-src/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming .github/skills/output-dev-llm-streaming && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "output-dev-llm-streaming" agent skill from https://github.com/growthxai/output/tree/main/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming into .github/skills/output-dev-llm-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "output-dev-llm-streaming", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add growthxai/output --skill output-dev-llm-streaming -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install growthxai/output output-dev-llm-streaming --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/growthxai/output.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming .opencode/skills/output-dev-llm-streaming && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "output-dev-llm-streaming" agent skill from https://github.com/growthxai/output/tree/main/coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming into .opencode/skills/output-dev-llm-streaming/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "output-dev-llm-streaming", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: output-dev-llm-streaming
GitHub stars: 442
Token cost: ~1.2k tokens
SKILL.md length: 409 words
Files: 1
Skills in repo: 50
Repo updated: Oct 9, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Implement LLM text streaming in Output workflow steps with generateTextWithStreaming, Agent.generateWithStreaming, streamText, or Agent.stream.

Adding token progress
SKILL.md covers When to Use This Skill, Choose the API, generateTextWithStreaming() and Agent.generateWithStreaming(), plus 3 more sections
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
OnChunk callbacks

What it does

Output Dev LLM Streaming is an agent skill from growthxai/output. Implement LLM text streaming in Output workflow steps with generateTextWithStreaming, Agent.generateWithStreaming, streamText, or Agent.stream. Use when adding token progress, onChunk callbacks, or handling streamText onEnd/onError with Temporal retries.

Its SKILL.md is about 1.2k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

The repository describes itself as: The open-source TypeScript framework for building AI workflows and agents. Designed for Claude Code describe what you want, Claude builds it, with all the best practices already… The licence is Apache-2.0.

When your agent uses it

Adding token progress
OnChunk callbacks
Handling streamText onEnd/onError with Temporal retries

Example prompts

“/output-dev-llm-streaming”

Requirements

Pre-approved tools (allowed-tools): Read, Write, Edit

What it can do on your machine

Read from SKILL.md and the folder at commit 99ee298. 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
- Write
- Edit
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are typescript).
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 no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Output Dev LLM Streaming loads about 1.2k tokens when it runs. Until then it costs about 70 tokens; SKILL.md has 409 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~70
When it runs · the whole SKILL.md, loaded when a task matches: ~1.2k

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 growthxai/output at commit 99ee298, republished under its Apache-2.0 licence (© growthxai). 409 words, ~1,190 tokens.

Download SKILL.mdSave it as .claude/skills/output-dev-llm-streaming/SKILL.md (or your agent's skills folder).

name: output-dev-llm-streaming
description: Implement LLM text streaming in Output workflow steps with generateTextWithStreaming, Agent.generateWithStreaming, streamText, or Agent.stream. Use when adding token progress, onChunk callbacks, or handling streamText onEnd/onError with Temporal retries.
allowed-tools: Read, Write, Edit

LLM Text Streaming

When to Use This Skill

Adding token or chunk progress to an LLM-powered step
Choosing between completed generation and direct stream access
Using onChunk, or onEnd / onError on streamText() / Agent.stream()
Making stream failures trigger Temporal activity retries
Streaming Agent responses or persisting streamed conversations

Choose the API

Need	Use
Complete single-shot result	`generateText()`
Complete result plus `onChunk` progress	`generateTextWithStreaming()`
Direct access to `textStream` or `stream`	`streamText()`
Complete Agent result plus `onChunk` progress	`Agent.generateWithStreaming()`
Direct access to the Agent stream	`Agent.stream()`

In workflow steps, prefer generateTextWithStreaming() or Agent.generateWithStreaming() when onChunk progress is sufficient. They consume the stream internally, return complete results like generateText() or Agent.generate(), and reject on provider, transport, or abort errors. Rejection allows Temporal to record the failed activity attempt and apply the step retry policy.

streamText() and Agent.stream() remain supported for code that needs direct control over stream consumption.

generateTextWithStreaming()

typescript

import { generateTextWithStreaming } from '@outputai/llm';

const result = await generateTextWithStreaming( {
  prompt: 'draft@v1',
  variables: { topic },
  onChunk( { chunk } ) {
    if ( chunk.type === 'text-delta' ) {
      process.stdout.write( chunk.text );
    }
  }
} );

return result.result;

The result has the same complete response fields as generateText(), including result, text, output, usage, finishReason, and cost. Structured output passed with aiSdk.Output.* is available through result.output.

Agent.generateWithStreaming()

typescript

const result = await agent.generateWithStreaming( {
  onChunk( { chunk } ) {
    if ( chunk.type === 'text-delta' ) {
      process.stdout.write( chunk.text );
    }
  }
} );

generateWithStreaming() returns a complete Agent response and automatically stores messages when the Agent has a messageStore.

Show full SKILL.md (220 more words)Show less

Direct stream error handling

AI SDK streaming delivers provider and transport failures through onError. Iterating textStream does not reliably throw the original error. When using streamText() in a workflow step, capture the error and throw it after consumption:

typescript

import { streamText } from '@outputai/llm';

const captured: { error: unknown } = { error: null };
const result = streamText( {
  prompt: 'draft@v1',
  variables: { topic },
  onError( { error } ) {
    captured.error = error;
  }
} );

const chunks: string[] = [];
for await ( const chunk of result.textStream ) {
  chunks.push( chunk );
}

if ( captured.error ) {
  throw captured.error;
}

return chunks.join( '' );

Registering onError without throwing the captured error can let the step return an empty successful result, preventing Temporal from retrying it. Awaiting a completion property may also produce a generic no-output error instead of the original provider error.

Agent.stream() stores conversation messages in its wrapped onEnd when finishReason is not 'error'. Use Agent.generateWithStreaming() when a complete stored response meets the requirement.

Streaming call arguments: prompt, promptDir, variables, tools, output, toolChoice, stopWhen, abortSignal, plus onChunk (generateTextWithStreaming) or onChunk / onEnd / onError (streamText). Agent methods: messages, abortSignal, toolChoice, plus those same stream callbacks.

Rules

Prefer the completed streaming APIs in Temporal steps unless direct stream access is required.
Do not rely on onError alone to fail a step using streamText().
Throw the captured error only after stream consumption finishes.
Keep onChunk side effects bounded. A Temporal signal per token creates a history event per signal, so batch high-frequency updates.
Do not describe streamText() or Agent.stream() as deprecated.

output-dev-step-function - Put LLM calls inside Temporal activity steps
output-dev-agent-class - Construct and use reusable Agents
output-dev-prompt-file - Create prompt files for generation
output-error-try-catch - Handle step and workflow failures

Files

Just SKILL.md in coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming of growthxai/output.

Open the folder on GitHubat commit 99ee298

Compare with similar skills

Output Dev LLM Streaming 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.

Output Dev LLM Streaming compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Output Dev LLM Streaming this skillgrowthxai/output	442	—	~1.2k	Automated safety check: Pass	Apache-2.0	today
Implementsickn33/agentic-awesome-skills	47k	5 repos	~306	Automated safety check: Pass	MIT	yesterday
Implementcodewhale-hq/Codewhale	41k	—	~190	Automated safety check: Pass	MIT	today
Os Step By Stepkharmanskyi/open-steps	1.3k	—	~1.9k	Automated safety check: Pass	MIT	5 days ago
Structured Step By Step Reasoningaiming-lab/MetaClaw	3.5k	—	~212	Automated safety check: Pass	MIT	4 mo ago
Cuda Streamspytorch/pytorch	104k	—	~796	Automated safety check: Pass	Custom licence	today

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Questions about Output Dev LLM Streaming

What does Output Dev LLM Streaming do?

Implement LLM text streaming in Output workflow steps with generateTextWithStreaming, Agent.generateWithStreaming, streamText, or Agent.stream. Output Dev LLM Streaming is an agent skill from growthxai/output.stream.

When should I use Output Dev LLM Streaming?

Output Dev LLM Streaming fits situations like: adding token progress; onChunk callbacks; handling streamText onEnd/onError with Temporal retries.

How do I install Output Dev LLM Streaming in Claude Code?

Run `npx skills add growthxai/output --skill output-dev-llm-streaming -a claude-code`. Or copy the skill folder (coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming in growthxai/output) into .claude/skills/output-dev-llm-streaming in your project. Claude Code loads it when a task matches its description.

How do I install Output Dev LLM Streaming in Codex?

Run `npx skills add growthxai/output --skill output-dev-llm-streaming -a codex`. Or copy the skill folder (coding_assistants/claude/plugins/outputai/skills/output-dev-llm-streaming in growthxai/output) into .agents/skills/output-dev-llm-streaming in your project. Codex loads it when a task matches its description.

Can I use Output Dev LLM Streaming 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 growthxai/output --skill output-dev-llm-streaming -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/output-dev-llm-streaming, .gemini/skills/output-dev-llm-streaming, .github/skills/output-dev-llm-streaming and .opencode/skills/output-dev-llm-streaming in your project.

What does Output Dev LLM Streaming need to run?

SKILL.md names no scripts, command-line tools or credentials: Output Dev LLM Streaming is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit.

Does Output Dev LLM Streaming 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 Output Dev LLM Streaming 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 Output Dev LLM Streaming use?

Output Dev LLM Streaming is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Output Dev LLM Streaming use?

About 1.2k tokens (SKILL.md is roughly 4.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Output Dev LLM Streaming?

Skills that share tags, products or a category with Output Dev LLM Streaming: Implement (sickn33/agentic-awesome-skills, 47k stars), Implement (codewhale-hq/Codewhale, 41k stars), Os Step By Step (kharmanskyi/open-steps, 1.3k stars) and Structured Step By Step Reasoning (aiming-lab/MetaClaw, 3.5k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Output Dev LLM Streaming?

growthxai (a GitHub organization) maintains it in growthxai/output, which has 442 GitHub stars. The repository holds 50 skills in this directory. The repository was last updated on October 9, 2026.

Source: growthxai/output on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Output Dev LLM Streaming

Install Output Dev LLM Streaming

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

LLM Text Streaming

When to Use This Skill

Choose the API

generateTextWithStreaming()

Agent.generateWithStreaming()

Direct stream error handling

Rules

Files

Compare with similar skills

Similar skills

Implement

Implement

Os Step By Step

Structured Step By Step Reasoning

Cuda Streams

Incremental Implementation

More from growthxai/output

Output Build Workflow

Output Credentials Edit

Output Credentials Env Vars

Output Credentials Init

Output Debug Workflow

Output Dev Agent Class

Questions about Output Dev LLM Streaming

Install Output Dev LLM Streaming

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

LLM Text Streaming

When to Use This Skill

Choose the API

generateTextWithStreaming()

Agent.generateWithStreaming()

Direct stream error handling

Rules

Related Skills

Files

Compare with similar skills

Similar skills

More from growthxai/output

Questions about Output Dev LLM Streaming