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 are the foundation of goal-driven agents in Aden. They define WHAT your agent should achieve, not HOW.
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=[...],
)
Defining Success Criteria
Success criteria are measurable conditions that determine if your agent succeeded.
Structure
SuccessCriterion(
id="unique-id",
description="Human-readable description",
metric="how to measure",
target="target value",
weight=1.0, # Relative importance (0-1)
)
Metric Types
| Metric | Use Case | Example Target |
|---|
output_contains | Check if output has specific content | "success" |
output_equals | Exact match | "expected_value" |
llm_judge | LLM evaluates quality | ">= 0.8" |
custom | Custom evaluation function | varies |
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,
),
]
Defining Constraints
Constraints are boundaries your agent must respect during execution.
Constraint Types
| Type | Meaning | Effect |
|---|
hard | Must not violate | Violation = failure |
soft | Should avoid violating | Violation = warning |
Categories
time - Execution time limitscost - Token/API cost limitssafety - Safety requirementsscope - What the agent should/shouldn’t doquality - Quality requirements
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",
),
]
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",
},
)
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
Next Steps
Node Types
Learn about LLM, Router, Function, and Human nodes
Edge Configuration
Configure success, failure, and conditional edges
