tools-only Decision Record
A record of design and API decisions with their rationale, enabling prior decisions to guide future ones.
Hooks as Low-Level Primitives, Not High-Level Abstractions
Date: Jan 6, 2026
Decision
Hooks serve as low-level extensibility primitives for the agent loop. High-level constructs SHOULD be built on top of hooks rather than exposing HookProvider as the sole developer-facing interface. These higher-level constructs should define their own interface with domain-specific methods and type signatures beyond what HookProvider alone provides.
Rationale
Exposing only HookProvider directly to consumers adds complexity to the implementor while offering no guidance on implementation requirements or type safety for specific use cases.
For example, an Agent-provided retry_strategy should not be implemented as:
def Agent.__init__(
...
retry_strategy: HookProvider
)
This is too low-level and gives no guidance on how a retry strategy should be implemented. Instead, a specific interface or base class should be built on top of hooks, providing additional scaffolding:
class RetryStrategy(HookProvider):
def register_hooks(registry):
...
@abstractmethod
def should_retry_model(e: Exception) -> bool:
"""Return true if the model call should be retried based on this exception"""
...
def calculate_retry_delay(attempt: int) -> int:
...
Higher-level abstractions require additional interface definitions, but this tradeoff provides an improved developer experience through explicit contracts. Developers with edge cases can still drop to raw HookProvider (and agent.hooks) when needed — optimizing for the common path while preserving that escape hatch.
Prefer Flat Namespaces Over Nested Modules
Date: Jan 16, 2026
Decision
Public APIs should expose commonly-used functionality through flat, top-level namespaces rather than requiring users to import from deeply nested module paths.
Rationale
Fewer imports are simpler to use and more discoverable when using IDE autocompletion & documentation. While inspired by Python's "Flat is better than nested" (PEP 20 - The Zen of Python), this principle applies across SDK languages.
We don't want users continually importing additional modules for common functionality. The goal is to optimize for the 80% case where users need standard features, while still allowing advanced users to import from specific submodules when needed.
For example, we prefer exporting all hook events from a single module:
from strands.hooks import MultiAgentInitializedEvent
instead of categorizing them based on their purpose
from strands.hooks.multiagent import MultiAgentInitializedEvent
this is even more important when the event names already indicate their grouping (MultiAgentInitializeEvent).
Internal module organization can remain nested for code maintainability — the key is re-exporting public symbols at common locations.
When Internal Interfaces Should Extend HookProvider
Date: Jan 21, 2026
Decision
Internal interfaces that integrate with the agent lifecycle (such as RetryStrategy, SessionManager, and ConversationManager) SHOULD extend HookProvider. When uncertain whether a new interface requires HookProvider, prefer a simple domain interface—it can always be evolved to extend HookProvider later, but the reverse migration breaks existing implementations.
Rationale
The team considered two approaches for RetryStrategy: extending HookProvider or exposing a simple domain interface with methods like should_retry(exception, attempt) -> bool.
While RetryStrategy is simple enough that a non-HookProvider interface would suffice, extending HookProvider maintains a uniform pattern across all agent constructor parameters that integrate with the lifecycle. Users implementing any of these interfaces learn one composition model. This aligns with the composability tenet: primitives are building blocks with each other.
The tradeoff is that HookProvider exposure can leak implementation details for interfaces with single decision points. Use the following criteria for future interfaces:
Use a simple interface when:
- The interface has a single responsibility expressible as one or two methods
- The interface does not need to respond to multiple lifecycle events
- Consistency with existing interfaces is not a priority
Extend HookProvider when:
- The capability requires responding to multiple distinct lifecycle events
- Users need to customize which events to subscribe to or add callbacks beyond base class defaults
Provide Both Low-Level and High-Level APIs
Date: Jan 30, 2026
Decision
When introducing new features, we SHOULD provide both low-level APIs that offer fine-grained control and high-level APIs that simplify common use cases. Low-level APIs serve as building blocks for power users and edge cases, while high-level APIs guide most users toward the happy path with opinionated defaults.
Rationale
Our tenets emphasize being extensible by design and simple at any scale. These goals can appear to conflict: maximum extensibility often requires exposing implementation details, while simplicity favors hiding them. A tiered API approach resolves this tension.
Low-level APIs provide fine-grained control, building blocks for custom implementations, and escape hatches for edge cases. They require deeper understanding of the underlying concepts but enable use cases the high-level API doesn't anticipate.
High-level APIs provide opinionated defaults for common use cases and reduced cognitive load. They push users toward the pit of success — the easy path is also the correct path. Most users should reach for these first.
For example, BidiAgent exposes send/receive as low-level APIs. Using them directly requires managing concurrency, lifecycle, and event routing:
await agent.start()
async def read_input():
while True:
event = await input_source.read()
await agent.send(event)
asyncio.create_task(read_input())
async for event in agent.receive():
...
await agent.stop()
The run method builds on these to abstract the complexity. Users provide IO callbacks and the method handles the rest:
await agent.run(inputs=[audio_input], outputs=[audio_output, text_output])
This pattern aligns with progressive disclosure from UX design: show users what they need for common tasks while making advanced capabilities discoverable when needed.