Comprehensive guide to Output.ai Framework for building durable, LLM-powered workflows orchestrated by Temporal. Covers project structure, workflow patterns, steps, LLM integration, HTTP clients, CLI commands, and the full inventory of available agents, commands, and skills.
Scanned 5/27/2026
Install via CLI
openskills install growthxai/output---
name: output-meta-project-context
description: Comprehensive guide to Output.ai Framework for building durable, LLM-powered workflows orchestrated by Temporal. Covers project structure, workflow patterns, steps, LLM integration, HTTP clients, CLI commands, and the full inventory of available agents, commands, and skills.
allowed-tools: [Read]
---
# Output.ai Framework - Complete Project Context
## What is Output.ai?
Output.ai provides infrastructure for building production-grade AI workflows: fact checkers, content generators, data extractors, research assistants, and multi-step agents. Built on Temporal, it guarantees **durable execution** - if execution fails mid-run, it resumes from the last successful step.
## Core Philosophy
**Separation of orchestration from I/O:**
- **Workflows** orchestrate execution (must be deterministic - no I/O)
- **Steps/Evaluators** handle all I/O operations (HTTP, LLM, database calls)
This separation enables automatic retries, resumption, and debugging.
## Component Taxonomy
| Component | Purpose | Key Rule |
|-----------|---------|----------|
| **Workflow** | Orchestrates step execution | Must be deterministic (no I/O, no Date.now(), no Math.random()) |
| **Step** | Handles all I/O operations | Where HTTP, LLM, DB calls happen |
| **Evaluator** | Quality assessment | Returns confidence-scored results for validation loops |
| **Scenario** | Test input data | JSON files matching workflow's inputSchema |
| **Prompt** | LLM templates | Liquid.js templating with YAML frontmatter config |
| **Eval Test** | Offline quality testing | Dataset-driven verification with `verify()` from `@outputai/evals` |
## Project Structure
```
config/
├── credentials.yml.enc # Global encrypted credentials
├── credentials.key # Global decryption key (DO NOT COMMIT)
└── credentials/ # Environment-specific credentials
├── production.yml.enc
└── production.key
src/
├── shared/ # Shared code across workflows
│ ├── clients/ # API clients (e.g., jina.ts, stripe.ts)
│ └── utils/ # Utility functions (e.g., string.ts)
└── workflows/ # Workflow definitions
└── {workflow_name}/
├── workflow.ts # Orchestration logic (deterministic)
├── steps.ts # I/O operations
├── types.ts # Zod schemas (input, output, internal)
├── evaluators.ts # Quality checks (optional)
├── utils.ts # Local utilities (optional)
├── credentials.yml.enc # Workflow-specific credentials (optional)
├── prompts/ # LLM templates (optional)
│ └── generate@v1.prompt
├── scenarios/ # Test inputs (optional)
│ └── happy_path.json
└── tests/ # Offline eval tests (optional)
├── datasets/ # YAML test datasets
│ └── happy_path.yml
└── evals/ # Eval evaluators and workflow
├── evaluators.ts
└── workflow.ts
```
## Code Reuse Rules
**Shared directory** (`src/shared/`):
- `shared/clients/` - API clients using `@outputai/http` for external services
- `shared/utils/` - Helper functions and utilities
**Allowed imports:**
- Workflows/steps can import from `../../shared/clients/*.js` and `../../shared/utils/*.js`
- Workflows/steps can import from local files (`./types.js`, `./utils.js`)
**Forbidden:**
- Importing from sibling workflow folders (`../other_workflow/steps.js`)
- Steps importing other steps (activity isolation requirement)
## Critical Rules
| Rule | Correct | Incorrect |
|------|---------|-----------|
| Zod import | `import { z } from '@outputai/core'` | `import { z } from 'zod'` |
| HTTP client | `import { httpClient } from '@outputai/http'` | `import axios from 'axios'` |
| Credentials | `import { credentials } from '@outputai/credentials'` | `process.env.SECRET` |
| LLM calls | `import { generateText, Output } from '@outputai/llm'` | Direct provider SDK |
| ES imports | `import { fn } from './file.js'` | `import { fn } from './file'` |
| Workflow I/O | Call steps for any I/O | Direct fetch/http in workflow |
**Determinism violations (never in workflows):**
- `Date.now()`, `new Date()`
- `Math.random()`, `crypto.randomUUID()`
- Direct HTTP/fetch calls
- File system operations
- Environment variable reads
---
## Available Tools Inventory
### Agents
| Agent | Purpose |
|-------|---------|
| `workflow-planner` | Designs workflow architecture, creates implementation blueprints |
| `workflow-debugger` | Analyzes workflow execution traces, identifies issues |
| `workflow-quality` | Reviews code quality, validates implementations |
| `workflow-prompt-writer` | Creates and optimizes LLM prompt templates |
| `workflow-context-fetcher` | Gathers documentation and existing patterns |
### Commands
| Command | Purpose | When to Use |
|---------|---------|-------------|
| `/output-plan-workflow` | Plan workflow architecture | **ALWAYS FIRST** - creates implementation blueprint |
| `/output-build-workflow` | Build/implement workflows | After planning, or for modifications |
| `/output-debug-workflow` | Debug workflow issues | When workflows fail or behave unexpectedly |
### Skills
#### Workflow Operations
| Skill | Purpose |
|-------|---------|
| `output-workflow-run` | Synchronous workflow execution (waits for result) |
| `output-workflow-start` | Asynchronous workflow execution (returns ID) |
| `output-workflow-list` | List available workflows |
| `output-workflow-status` | Check async workflow status |
| `output-workflow-result` | Get async workflow result |
| `output-workflow-reset` | Rerun a workflow from after a completed step |
#### Monitoring & Debugging
| Skill | Purpose |
|-------|---------|
| `output-workflow-stop` | Stop running workflow |
| `output-workflow-trace` | Trace workflow execution |
| `output-workflow-runs-list` | List workflow run history |
| `output-dev-workflow-cost` | Calculate cost of a workflow run |
| `output-services-check` | Verify Output services status |
#### Error Diagnosis
| Skill | Catches |
|-------|---------|
| `output-error-zod-import` | Wrong zod import source |
| `output-error-nondeterminism` | Date.now, Math.random in workflows |
| `output-error-try-catch` | Missing error handling in steps |
| `output-error-missing-schemas` | Incomplete Zod schema exports |
| `output-error-direct-io` | I/O operations in workflow files |
| `output-error-http-client` | Using axios instead of @outputai/http |
#### Meta/Lifecycle
| Skill | Purpose |
|-------|---------|
| `output-meta-pre-flight` | Pre-operation validation checks |
| `output-meta-post-flight` | Post-operation verification |
| `output-meta-project-context` | Load full project context (this skill) |
#### Development
| Skill | Purpose |
|-------|---------|
| `output-dev-folder-structure` | Project and workflow directory layout |
| `output-dev-workflow-function` | Writing deterministic workflow files |
| `output-dev-step-function` | Writing step functions for I/O |
| `output-dev-types-file` | Zod schema definitions |
| `output-dev-evaluator-function` | Quality assessment functions |
| `output-dev-eval-testing` | Offline eval tests with `@outputai/evals` |
| `output-dev-prompt-file` | LLM prompt templates with Liquid.js |
| `output-dev-model-selection` | Pick a current LLM model via the AI Gateway listing |
| `output-dev-upgrade-prompt-models` | Bulk-upgrade `model:` fields across `.prompt` files |
| `output-dev-scenario-file` | Test input JSON files |
| `output-dev-http-client-create` | Shared HTTP API client patterns |
| `output-dev-create-skeleton` | Generate workflow skeleton |
#### Credentials
| Skill | Purpose |
|-------|---------|
| `output-dev-credentials` | Full credentials system reference (API, scopes, merging, custom providers) |
| `output-credentials-init` | Initialize encrypted credentials files for the first time |
| `output-credentials-edit` | View and edit credential values with `show`/`get`/`edit` commands |
| `output-credentials-env-vars` | Wire credentials to env vars using the `credential:` convention |
---
## CLI Quick Reference
```bash
# Development
npx output dev # Start dev environment
# List & inspect
npx output workflow list # List available workflows
# Execute
npx output workflow run <name> --input '{}' # Run synchronously (waits)
npx output workflow start <name> --input '{}' # Run async (returns ID)
npx output workflow status <id> # Check async status
npx output workflow result <id> # Get async result
# Debug
npx output workflow debug <id> # Debug failed workflow
npx output workflow debug <id> --format json # Machine-readable output
# Rerun from a step (replays up to <stepName>, re-executes everything after)
npx output workflow reset <id> --step <stepName>
npx output workflow reset <id> --step <stepName> --reason "why"
# Eval Testing
npx output workflow test <name> # Run eval tests against datasets
npx output workflow test <name> --cached # Use cached output (fast)
npx output workflow test <name> --save # Run fresh and save results
npx output workflow dataset list <name> # List datasets for a workflow
npx output workflow dataset generate <name> --input '{}' # Generate dataset
# Credentials
npx output credentials init # Initialize encrypted credentials
npx output credentials edit # Edit credentials (decrypts, opens $EDITOR)
npx output credentials show # Show decrypted credentials
npx output credentials get <path> # Get single credential value
```
---
## Naming Conventions
| Element | Convention | Example |
|---------|------------|---------|
| Workflow folder | snake_case | `fact_checker/` |
| Workflow name | snake_case | `name: 'fact_checker'` |
| Step functions | camelCase | `fetchArticle()`, `analyzeContent()` |
| Schema names | PascalCase | `InputSchema`, `ArticleData` |
| Prompt files | snake_case@version.prompt | `analyze_claim@v1.prompt` |
| Scenario files | snake_case.json | `happy_path.json` |
---
## Common Patterns
### Workflow Pattern
```typescript
import { workflow, z } from '@outputai/core';
import { fetchData, processData } from './steps.js';
export const inputSchema = z.object( { url: z.string().url() } );
export const outputSchema = z.object( { result: z.string() } );
export default workflow( {
name: 'my_workflow',
description: 'Processes data from URL',
inputSchema,
outputSchema,
fn: async input => {
const data = await fetchData( input.url );
const result = await processData( data );
return { result };
}
} );
```
See `output-dev-workflow-function` for comprehensive patterns.
### Step Pattern
```typescript
import { step, z } from '@outputai/core';
import { httpClient } from '@outputai/http';
export const fetchData = step(
{ name: 'fetchData', inputSchema: z.string(), outputSchema: z.any() },
async url => {
const client = httpClient( { prefixUrl: url } );
const response = await client.get( '' );
return response.json();
}
);
```
See `output-dev-step-function` for comprehensive patterns.
### HTTP Client Pattern (Shared)
Clients live in `src/shared/clients/` and are shared across all workflows.
```typescript
// src/shared/clients/example.ts
import { FatalError, ValidationError } from '@outputai/core';
import { httpClient } from '@outputai/http';
import { credentials } from '@outputai/credentials';
const API_KEY = credentials.require( 'example.api_key' );
const client = httpClient( {
prefixUrl: 'https://api.example.com',
headers: { Authorization: `Bearer ${API_KEY}` },
timeout: 30000,
retry: { limit: 3, statusCodes: [ 408, 429, 500, 502, 503, 504 ] }
} );
export async function fetchFromExample( query: string ): Promise<ExampleResponse> {
try {
const response = await client.get( 'endpoint', { searchParams: { q: query } } );
return response.json();
} catch ( error: unknown ) {
const err = error as { status?: number; message?: string };
if ( err.status === 401 || err.status === 403 ) {
throw new FatalError( `Auth failed: ${err.message}` );
}
throw new ValidationError( `Request failed: ${err.message}` );
}
}
```
**Error type guidelines:**
- `FatalError`: 401, 403, 404 (won't succeed on retry)
- `ValidationError`: 429, 5xx (may succeed on retry)
See `output-dev-http-client-create` for comprehensive patterns.
### Evaluator Pattern
Evaluators return confidence-scored results. Three result types available:
```typescript
import { evaluator, z, EvaluationBooleanResult, EvaluationNumberResult, EvaluationStringResult } from '@outputai/core';
// Boolean evaluator - pass/fail checks
export const evaluateCompleteness = evaluator( {
name: 'evaluate_completeness',
description: 'Check if content meets minimum length',
inputSchema: z.object( { content: z.string(), minLength: z.number() } ),
fn: async ( { content, minLength } ) => {
return new EvaluationBooleanResult( {
value: content.length >= minLength,
confidence: 1.0,
reasoning: `Content has ${content.length} chars (min: ${minLength})`
} );
}
} );
```
See `output-dev-evaluator-function` for comprehensive patterns.
### Prompt File Pattern
Prompts use YAML frontmatter + Liquid.js templating. Location: `src/workflows/{name}/prompts/`
```
---
provider: anthropic
# current as of 2026-05-04 — run output-dev-model-selection for the latest
model: claude-sonnet-4-6
temperature: 0.7
maxTokens: 4096
---
<system>
You are an expert content analyzer.
{% if context %}
Additional context: {{ context }}
{% endif %}
</system>
<user>
Analyze the following content:
<content>
{{ content }}
</content>
Provide {{ numberOfPoints | default: 3 }} key insights.
</user>
```
**Using in steps:**
```typescript
import { generateText, Output } from '@outputai/llm';
import { z } from '@outputai/core';
// Structured output
const { output } = await generateText( {
prompt: 'analyze@v1',
variables: { content: 'Article text...', numberOfPoints: 5 },
output: Output.object( {
schema: z.object( { insights: z.array( z.string() ) } )
} )
} );
// Text output
const { result } = await generateText( {
prompt: 'summarize@v1',
variables: { content: 'Article text...' }
} );
```
**Provider & model selection:** the SDK supports `anthropic`, `openai`, `vertex`, `bedrock`, `azure`, and `perplexity` (see [sdk/llm/src/ai_model.js](../../../../../../sdk/llm/src/ai_model.js) for the registered list). Don't pin specific model IDs in docs — they drift. To pick a current model, run [`output-dev-model-selection`](../output-dev-model-selection/SKILL.md), which queries the AI Gateway model index live.
See `output-dev-prompt-file` for comprehensive patterns.
---
## Practical Tips
### Docker & Services
- **Restart worker after adding workflows**: `docker restart <project>-worker-1`
- **View worker logs**: `docker logs -f output-worker-1`
- **Check services**: Use `output-services-check` skill
### Payload Limits
- Temporal: ~2MB per workflow input/output
- gRPC: ~4MB maximum
- For larger data, use file storage and pass references
### Debugging Workflow Failures
1. Get the workflow ID from error output
2. Run `npx output workflow debug <id> --format json`
3. Look for: failed step name, error message, input that caused failure
4. Check if issue is determinism, schema validation, or external API
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