oh-my-dag

★ 44

api

★ 15

oh-my-dag vs api

Q: Which is better, oh-my-dag or api?

By GitHub stars, oh-my-dag has more community adoption, but the best choice depends on your specific use case.

oh-my-dag: Oh-my-dag (omd) serves as an orchestration layer beneath your AI coding agent, transforming conversational tasks into structured, checkpointed DAGs. It enforces rigorous verification through exit codes, cross-model critiques, and artifact gates, ensuring the reliability and correctness of agent-generated work.; api: iblai/api is a toolkit enabling AI agents to operate the ibl.ai platform through its REST API, offering skills for agent configuration, data management, and platform administration. It includes a hosted MCP server for real-time agent chat, allowing headless platform control without a UI.

TL;DR

oh-my-dagWorkflow Automation · ★ 44

Deep Research & Analysis: Conduct multi-stage research pipelines involving seeded crawls, fan-out lenses, judge panels, and gap rounds using different models for each stage.

Read oh-my-dag full review →

apiWorkflow Automation · ★ 15

Programmatically configure AI agents (LLM, prompts, skills, safety, privacy).

Read api full review →

Side-by-Side Comparison

Field

oh-my-dag

api

Features

oh-my-dag

01Exit Code as Finish Line: Tasks conclude when a declared command exits successfully, preventing models from self-certifying completion.

02Rigorous Criterion Verification: Acceptance tests run against pre-work and deliberately wrong artifacts to ensure they genuinely test the solution.

03Multi-Model Orchestration: Allows different LLMs for each node in a DAG, enabling tailored model selection and cross-family second opinions for critical tasks.

04Resumable & Checkpointed Workflows: Every completed node is atomically saved to disk, allowing interrupted work to resume from the last checkpoint, saving time and billing.

05LLM-Free Retrieval: `omd_web` performs web searches and fetches without an LLM in the loop, ensuring factual accuracy based on retrieved content rather than model memory.

api

01Drive ibl.ai platform REST API directly from AI agents.

02Manage agents, datasets, memory, users, roles, and notifications.

03Authenticate once and target any of your ibl.ai organizations.

04Includes a hosted Model Context Protocol (MCP) server for live agent chat.

05Operate the platform headless, from CI, a terminal, or any MCP-capable assistant.

Use Cases

oh-my-dag

↳Deep Research & Analysis: Conduct multi-stage research pipelines involving seeded crawls, fan-out lenses, judge panels, and gap rounds using different models for each stage.

↳Automated Design Argumentation & Specification: Argue design choices and then generate executable specifications (e.g., `/omd-grill` followed by `/omd-contract`).

↳Cross-Model Code Review: Perform multi-dimensional code reviews, falsifying findings across different models to ensure comprehensive and unbiased feedback (`/omd-review`).

↳Automated Debugging Workflows: Systematically reproduce issues, lock scope, test parallel hypotheses, and verify fixes (`/omd-debug`).

↳Controlled Delivery of Decision Maps: Manage decision maps in Git, ruled by user-defined triggers, preventing unattended merging (`/omd-deliver`).

api

↳Programmatically configure AI agents (LLM, prompts, skills, safety, privacy).

↳Automate administration tasks like user management, role-based access control (RBAC), and integrations.

↳Manage training datasets (RAG) by adding, training, and deleting files/URLs.

↳Connect and interact with deployed AI agents in real-time for streamed responses.

↳Pull analytics and audit logs across agents, content, and users for monitoring.

FAQ

What is the difference between oh-my-dag and api?

Both oh-my-dag and api are in the Workflow Automation category. oh-my-dag has 44 stars, while api has 15 stars.

Which is better, oh-my-dag or api?

The best choice depends on your use case. Choose oh-my-dag if Deep Research & Analysis: Conduct multi-stage research pipelines involving seeded crawls, fan-out lenses, judge panels, and gap rounds using different models for each stage., and api if Programmatically configure AI agents (LLM, prompts, skills, safety, privacy)..

Is oh-my-dag free or open source?

Yes, oh-my-dag is open source on GitHub (MIT).

Is api free or open source?

Yes, api is open source on GitHub (MIT).

Cloud Infrastructure

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TL;DR

Side-by-Side Comparison

Features

Use Cases

FAQ

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