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Goals are the foundation of goal-driven agents in Aden. They define WHAT your agent should achieve, not HOW.
For the conceptual foundation behind goals and success criteria, see Outcome-Driven Development.

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What is a Goal?

A Goal contains:
  • Success Criteria - Measurable conditions that define success
  • Constraints - Boundaries the agent must respect
  • Context - Additional information for decision-making
from framework.graph.goal import Goal, SuccessCriterion, Constraint

goal = Goal(
    id="my-goal",
    name="My Agent Goal",
    description="What this agent should accomplish",
    success_criteria=[...],
    constraints=[...],
)

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Defining Success Criteria

Success criteria are measurable conditions that determine if your agent succeeded.

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Structure

SuccessCriterion(
    id="unique-id",
    description="Human-readable description",
    metric="how to measure",
    target="target value",
    weight=1.0,  # Relative importance (0-1)
)

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Metric Types

MetricUse CaseExample Target
output_containsCheck if output has specific content"success"
output_equalsExact match"expected_value"
llm_judgeLLM evaluates quality">= 0.8"
customCustom evaluation functionvaries

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Example

success_criteria = [
    SuccessCriterion(
        id="completeness",
        description="Response covers all requested topics",
        metric="llm_judge",
        target=">= 0.9",
        weight=0.5,
    ),
    SuccessCriterion(
        id="accuracy",
        description="Information is factually correct",
        metric="llm_judge",
        target=">= 0.95",
        weight=0.5,
    ),
]

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Defining Constraints

Constraints are boundaries your agent must respect during execution.

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Constraint Types

TypeMeaningEffect
hardMust not violateViolation = failure
softShould avoid violatingViolation = warning

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Categories

  • time - Execution time limits
  • cost - Token/API cost limits
  • safety - Safety requirements
  • scope - What the agent should/shouldn’t do
  • quality - Quality requirements

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Example

constraints = [
    Constraint(
        id="no-external-apis",
        description="Do not call external APIs without user approval",
        constraint_type="hard",
        category="safety",
    ),
    Constraint(
        id="response-length",
        description="Keep responses under 500 words",
        constraint_type="soft",
        category="quality",
    ),
]

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Complete Example

Here’s a complete goal for a research agent: 
from framework.graph.goal import Goal, SuccessCriterion, Constraint

research_goal = Goal(
    id="research-agent-goal",
    name="Technical Research Agent",
    description="Research technical topics and provide comprehensive summaries",
    
    success_criteria=[
        SuccessCriterion(
            id="topic-coverage",
            description="Covers all major aspects of the topic",
            metric="llm_judge",
            target=">= 0.9",
            weight=0.4,
        ),
        SuccessCriterion(
            id="source-quality",
            description="Uses credible sources",
            metric="llm_judge",
            target=">= 0.8",
            weight=0.3,
        ),
        SuccessCriterion(
            id="clarity",
            description="Output is clear and well-structured",
            metric="llm_judge",
            target=">= 0.85",
            weight=0.3,
        ),
    ],
    
    constraints=[
        Constraint(
            id="verify-sources",
            description="All information must be from verifiable sources",
            constraint_type="hard",
            category="quality",
        ),
        Constraint(
            id="no-speculation",
            description="Do not include unverified speculation",
            constraint_type="hard",
            category="safety",
        ),
        Constraint(
            id="time-limit",
            description="Complete research within 5 minutes",
            constraint_type="soft",
            category="time",
        ),
    ],
    
    required_capabilities=["web_search", "llm"],
    
    context={
        "domain": "technology",
        "audience": "developers",
    },
)

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Best Practices

Do

  • Use specific, measurable success criteria
  • Include 3-5 success criteria with different weights
  • Define hard constraints for critical requirements
  • Add context to help the agent make better decisions

Don't

  • Use vague criteria like “do a good job”
  • Skip constraints entirely
  • Set all weights to 1.0 (use relative importance)
  • Forget to specify required capabilities

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Next Steps

Node Types

Learn about LLM, Router, Function, and Human nodes

Edge Configuration

Configure success, failure, and conditional edges