> ## Documentation Index
> Fetch the complete documentation index at: https://docs.adenhq.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Goals and Outcomes

> Define measurable success criteria, constraints, and context for Hive agents

## The Core Idea

Hive is outcome-driven: you define what success looks like, and the agent adapts toward that result.

Instead of hardcoding every step, you define:

* A goal
* Success criteria (weighted quality checks)
* Constraints (hard and soft boundaries)
* Context (domain knowledge and preferences)

## Task-Driven vs Goal-Driven vs Outcome-Driven

| Paradigm       | Main Question                        | Limitation                                       |
| -------------- | ------------------------------------ | ------------------------------------------------ |
| Task-Driven    | "Did each step run?"                 | Correct steps can still produce poor results     |
| Goal-Driven    | "Are we aiming correctly?"           | Goals can be vague without measurable criteria   |
| Outcome-Driven | "Did we produce the desired result?" | Requires clear metrics and evaluation discipline |

## Goal as a Structured Contract

In Hive, a goal is a structured object with three parts.

### Success Criteria

Each criterion defines a measurable quality signal and a weight.

Common metrics:

* `output_contains`
* `output_equals`
* `llm_judge`
* `custom`

Weights allow trade-offs across multiple quality dimensions.

### Constraints

Constraints define non-negotiables and preferences.

* Hard constraints: violation triggers failure/escalation
* Soft constraints: violation is tolerated with warning/replan

Typical categories:

* `time`
* `cost`
* `safety`
* `scope`
* `quality`

### Context

Context supplies durable background information that should influence agent decisions and LLM behavior.

## Why This Model Matters

1. The agent can self-correct during execution against explicit criteria.
2. Evolution has a target because failures map to specific unmet criteria.
3. Humans retain control through hard constraints and intervention gates.

## Goal Lifecycle

Goals typically move through:

`DRAFT -> READY -> ACTIVE -> COMPLETED | FAILED | SUSPENDED`

## Related Concepts

* [Outcome-Driven Development](/building-agent/concepts/outcome-driven-development)
* [Agent Graph](/building-agent/concepts/agent-graph)
* [Evolution](/building-agent/concepts/evolution)