Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add growthxai/output --skill output-dev-types-filegit clone --depth 1 https://github.com/growthxai/outputWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/growthxai/output/output-dev-types-file)<a href="https://agentmods.dev/skills/growthxai/output/output-dev-types-file"><img src="https://agentmods.dev/badge/skills/growthxai/output/output-dev-types-file/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/growthxai/output/output-dev-types-file"><img src="https://agentmods.dev/badge/skills/growthxai/output/output-dev-types-file.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00035 | $0.02711 |
| Opus 5.5 | $0.00014 | $0.01084 |
| Sonnet 5.5 | $0.00007 | $0.00542 |
| Haiku 4.5 | $0.00003 | $0.00271 |
Grade A, and why
output-dev-types-file scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 315 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Creating types.ts Files with Zod Schemas
Overview
This skill documents how to create types.ts files for Output SDK workflows. These files contain Zod schemas for input/output validation and their corresponding TypeScript types.
When to Use This Skill
- Creating a new workflow's type definitions
- Adding new schemas for steps
- Fixing schema validation errors
- Refactoring existing type definitions
Critical Import Rule
ALWAYS import z from @outputai/core, NEVER from zod directly:
// CORRECT
import { z } from '@outputai/core';
// WRONG - will cause runtime errors
import { z } from 'zod';
Related Skill: output-error-zod-import for troubleshooting import issues
Basic Structure
import { z } from '@outputai/core';
// 1. Workflow Input Schema
export const WorkflowInputSchema = z.object( {
// Define input fields
} );
// 2. Workflow Output Type
export type WorkflowInput = z.infer<typeof WorkflowInputSchema>;
export type WorkflowOutput = /* output type */;
// 3. Step Schemas (for each step)
export const StepNameInputSchema = z.object( {
// Step input fields
} );
export const StepNameOutputSchema = z.object( {
// Step output fields
} );
// 4. Type Exports
export type StepNameInput = z.infer<typeof StepNameInputSchema>;
export type StepNameOutput = z.infer<typeof StepNameOutputSchema>;
CRITICAL: Schema Constraints for LLM Output
Schemas passed to aiSdk.Output.object() are sent to LLM providers as tool definitions. Anthropic rejects several JSON Schema constraints that Zod methods produce. Getting this wrong causes runtime errors.
What Is NOT Allowed in LLM Output Schemas
- Numbers:
.min(),.max()onz.number()produceminimum/maximum-- rejected by Anthropic. - Arrays:
.min(),.max(),.length()onz.array()produceminItems/maxItems-- Anthropic only supportsminItemsof0or1. Values like.length( 3 )or.min( 2 )will be rejected.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 1mo ago First seen · 315 lines · 35 tokens per session scan A 1cf466c1b95d
output-dev-types-file is a skill published in the GitHub repository growthxai/output (443 stars, last pushed today), licensed Apache-2.0. It adds 35 tokens to every session and 2,711 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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