lidangzzz/goal-driven

Health v2 · maintenance only

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Adoption not part of the score

1744 stars · 127 forks observed · 2026-10-20

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Goal-Driven is a prompt-based multi-agent methodology that wraps coding agents like Claude Code or Codex in a master-agent loop, keeping subagents working for hundreds of hours on a single verifiable goal. The master agent periodically evaluates subagent output against explicit success criteria and restarts work until the criteria are met.

Use cases

• run an AI agent for 100+ hours to build a compiler from specs
• have agents persistently solve a hard verifiable math or computational problem
• keep a coding agent from stopping early on a long complex task
• orchestrate master and subagent loops for goal completion checking
• generate large open-source projects like a SQLite clone with agents

When to choose

• your task has a clear goal and strict machine-checkable success criteria
• you use a multi-agent coding tool like Claude Code, Codex, or OpenClaw
• the problem is complex, long-running, and verifiable such as compilers or theorem proving

When to avoid

• your task is subjective or lacks well-defined completion criteria
• you need a quick one-shot coding assistant rather than a long autonomous run
• you cannot afford extended agent runtime and token costs

Facets

framework · maturity experimental

agent-framework llm-inference prompt-engineering developer-tools artificial-intelligence large-language-models developer-tools cli cross-platform multi-agent long-running-agents goal-driven claude-code codex autonomous-coding verification-loop ai-agents automation

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markdown · JSON · MCP: product_card(name="lidangzzz/goal-driven")