docs: add docstrings to Python adapter modules

packages/agent-os/src/agent_os/integrations/crewai_adapter.py

@@ -150,6 +150,22 @@ def _wrap_tool(self, tool, agent_name: str):
                 crew_name = self._crew_name
 
                 def governed_run(*args, **kwargs):
+                    """Governed wrapper around a CrewAI tool's run method.
+
+                    Intercepts the tool call, runs pre-execution policy checks,
+                    records the invocation in the audit log, and delegates
+                    to the original _run implementation.
+
+                    Args:
+                        *args: Positional arguments forwarded to the original tool.
+                        **kwargs: Keyword arguments forwarded to the original tool.
+
+                    Returns:
+                        The result from the original tool's run method.
+
+                    Raises:
+                        PolicyViolationError: If the tool call violates the active policy.
+                    """
                     request = ToolCallRequest(
                         tool_name=tool_name,
                         arguments=kwargs if kwargs else {"args": args},
@@ -194,6 +210,22 @@ def _wrap_agent(self, agent):
                     crew_name = self._crew_name
 
                     def governed_execute(task, *args, **kwargs):
+                        """Governed wrapper around a CrewAI agent's task execution.
+
+                        Intercepts each task execution call, applies pre-execution
+                        policy checks, and delegates to the original execute method.
+
+                        Args:
+                            task: The CrewAI Task object to execute.
+                            *args: Additional positional arguments.
+                            **kwargs: Additional keyword arguments.
+
+                        Returns:
+                            The task execution result from the underlying agent.
+
+                        Raises:
+                            PolicyViolationError: If the execution violates the active policy.
+                        """
                         task_id = getattr(task, 'id', None) or str(id(task))
                         logger.info("Agent task execution started: crew_name=%s, task_id=%s", crew_name, task_id)
                         if self._kernel.policy.require_human_approval:
@@ -253,6 +285,22 @@ def _intercept_task_steps(
 
             @functools.wraps(original_step)
             def governed_step(*args: Any, _orig=original_step, _attr=step_attr, **kwargs: Any) -> Any:
+                """Governed wrapper around a CrewAI task step.
+
+                Intercepts individual step calls within a task, validates
+                inputs against the active policy, and records each step
+                in the audit trail before delegating to the original method.
+
+                Args:
+                    *args: Positional arguments forwarded to the original step.
+                    **kwargs: Keyword arguments forwarded to the original step.
+
+                Returns:
+                    The result from the original step method.
+
+                Raises:
+                    PolicyViolationError: If the step input violates the active policy.
+                """
                 step_record = {
                     "crew": crew_name,
                     "agent": agent_name,
@@ -306,6 +354,22 @@ def _intercept_crew_memory(
 
                 @functools.wraps(save_fn)
                 def governed_save(*args: Any, _orig=save_fn, _mname=save_method_name, **kwargs: Any) -> Any:
+                    """Governed wrapper around CrewAI memory save operations.
+
+                    Validates content before it is written to crew memory,
+                    checking for PII patterns and policy-blocked content.
+                    Records every save attempt in the memory audit log.
+
+                    Args:
+                        *args: Positional arguments forwarded to the original save.
+                        **kwargs: Keyword arguments forwarded to the original save.
+
+                    Returns:
+                        The result from the original memory save method.
+
+                    Raises:
+                        PolicyViolationError: If the content contains PII or blocked patterns.
+                    """
                     combined = str(args) + str(kwargs)
 
                     # PII / secrets check
@@ -357,6 +421,22 @@ def _detect_crew_delegation(
 
         @functools.wraps(delegate_fn)
         def governed_delegate(*args: Any, **kwargs: Any) -> Any:
+            """Governed wrapper around CrewAI agent delegation.
+
+            Intercepts delegation calls between agents, tracks delegation
+            depth, and enforces the maximum delegation limit defined in
+            the active policy.
+
+            Args:
+                *args: Positional arguments forwarded to the original delegate.
+                **kwargs: Keyword arguments forwarded to the original delegate.
+
+            Returns:
+                The result from the delegated agent.
+
+            Raises:
+                PolicyViolationError: If the delegation depth exceeds the policy limit.
+            """
             depth = len(kernel._delegation_log) + 1
             if depth > max_depth:
                 raise PolicyViolationError(

packages/agent-os/src/agent_os/integrations/google_adk_adapter.py

@@ -233,9 +233,26 @@ def unwrap(self, governed_agent: Any) -> Any:
     # ------------------------------------------------------------------
 
     def _default_violation_handler(self, error: PolicyViolationError) -> None:
+        """Default handler called when a policy violation occurs.
+
+        Logs the violation at ERROR level. Override by passing a custom
+        on_violation callable to the kernel constructor.
+
+        Args:
+            error: The PolicyViolationError that was raised.
+        """
         logger.error(f"Policy violation: {error}")
 
     def _record(self, event_type: str, agent_name: str, details: dict[str, Any]) -> None:
+        """Append an audit event to the internal audit log.
+
+        Records the event only when log_all_calls is enabled.
+
+        Args:
+            event_type: Short string label for the event.
+            agent_name: Name of the ADK agent generating the event.
+            details: Arbitrary dict of additional context.
+        """
         if self._adk_config.log_all_calls:
             self._audit_log.append(
                 AuditEvent(
@@ -247,26 +264,55 @@ def _record(self, event_type: str, agent_name: str, details: dict[str, Any]) ->
             )
 
     def _check_tool_allowed(self, tool_name: str) -> tuple[bool, str]:
+        """Check whether a tool is permitted by the active ADK policy.
+
+        Args:
+            tool_name: Name of the ADK tool to check.
+
+        Returns:
+            Tuple of (allowed: bool, reason: str).
+        """
         if tool_name in self._adk_config.blocked_tools:
             return False, f"Tool '{tool_name}' is blocked by policy"
         if self._adk_config.allowed_tools and tool_name not in self._adk_config.allowed_tools:
             return False, f"Tool '{tool_name}' not in allowed list"
         return True, ""
 
     def _check_content(self, content: str) -> tuple[bool, str]:
+        """Scan a string for policy-blocked patterns.
+
+        Args:
+            content: The text to scan.
+
+        Returns:
+            Tuple of (allowed: bool, reason: str).
+        """
         content_lower = content.lower()
         for pattern in self._adk_config.blocked_patterns:
             if pattern.lower() in content_lower:
                 return False, f"Content matches blocked pattern: '{pattern}'"
         return True, ""
 
     def _check_timeout(self) -> tuple[bool, str]:
+        """Check whether the kernel has exceeded its configured timeout.
+
+        Returns:
+            Tuple of (within_limit: bool, reason: str).
+        """
         elapsed = time.time() - self._start_time
         if elapsed > self._adk_config.timeout_seconds:
             return False, f"Execution timeout ({elapsed:.0f}s > {self._adk_config.timeout_seconds}s)"
         return True, ""
 
     def _check_budget(self, cost: float = 1.0) -> tuple[bool, str]:
+        """Check whether a tool call would exceed the configured cost budget.
+
+        Args:
+            cost: Cost units to add for this call (default 1.0).
+
+        Returns:
+            Tuple of (within_budget: bool, reason: str).
+        """
         if self._adk_config.max_budget is not None:
             if self._budget_spent + cost > self._adk_config.max_budget:
                 return False, (
@@ -286,6 +332,17 @@ def _needs_approval(self, tool_name: str) -> bool:
         return True
 
     def _raise_violation(self, policy_name: str, description: str) -> PolicyViolationError:
+        """Create, record, and surface a PolicyViolationError.
+
+        Appends the error to the violations list and calls on_violation.
+
+        Args:
+            policy_name: Short identifier for the violated policy rule.
+            description: Human-readable description of the violation.
+
+        Returns:
+            The constructed PolicyViolationError (caller may raise it).
+        """
         error = PolicyViolationError(policy_name, description)
         self._violations.append(error)
         self.on_violation(error)

packages/agent-os/src/agent_os/integrations/guardrails_adapter.py

@@ -77,6 +77,12 @@ class ValidationOutcome:
     metadata: dict[str, Any] = field(default_factory=dict)
 
     def to_dict(self) -> dict[str, Any]:
+        """Serialise this outcome to a plain dictionary.
+
+        Returns:
+            A dict with validator, passed, and optionally error
+            and fixed_value keys.
+        """
         d: dict[str, Any] = {
             "validator": self.validator_name,
             "passed": self.passed,
@@ -101,9 +107,19 @@ class ValidationResult:
 
     @property
     def failed_validators(self) -> list[str]:
+        """Return the names of all validators that did not pass.
+
+        Returns:
+            List of validator name strings where passed is False.
+        """
         return [o.validator_name for o in self.outcomes if not o.passed]
 
     def to_dict(self) -> dict[str, Any]:
+        """Serialise this aggregated result to a plain dictionary.
+
+        Returns:
+            A dict with passed, action, outcomes, and failed_validators keys.
+        """
         return {
             "passed": self.passed,
             "action": self.action_taken.value,
@@ -128,9 +144,23 @@ def __init__(self, patterns: list[str], validator_name: str = "regex"):
 
     @property
     def name(self) -> str:
+        """Return the human-readable name of this regex validator.
+
+        Returns:
+            The validator name string used in audit logs and outcomes.
+        """
         return self._name
 
     def validate(self, value: str, metadata: dict[str, Any] | None = None) -> ValidationOutcome:
+        """Validate a string by checking it against blocked regex patterns.
+
+        Args:
+            value: The text to scan.
+            metadata: Optional dict of additional context (unused).
+
+        Returns:
+            ValidationOutcome indicating pass or fail.
+        """
 
         for pattern in self._patterns:
             match = pattern.search(value)
@@ -152,9 +182,23 @@ def __init__(self, max_length: int = 10000, validator_name: str = "length"):
 
     @property
     def name(self) -> str:
+        """Return the human-readable name of this length validator.
+
+        Returns:
+            The validator name string used in audit logs and outcomes.
+        """
         return self._name
 
     def validate(self, value: str, metadata: dict[str, Any] | None = None) -> ValidationOutcome:
+        """Validate that a string does not exceed the configured max length.
+
+        Args:
+            value: The text to check.
+            metadata: Optional dict of additional context (unused).
+
+        Returns:
+            ValidationOutcome with a fixed_value truncated to max_length on fail.
+        """
         if len(value) > self._max_length:
             return ValidationOutcome(
                 validator_name=self._name,
@@ -174,9 +218,23 @@ def __init__(self, blocked_keywords: list[str], validator_name: str = "keywords"
 
     @property
     def name(self) -> str:
+        """Return the human-readable name of this keyword validator.
+
+        Returns:
+            The validator name string used in audit logs and outcomes.
+        """
         return self._name
 
     def validate(self, value: str, metadata: dict[str, Any] | None = None) -> ValidationOutcome:
+        """Validate that a string contains none of the blocked keywords.
+
+        Args:
+            value: The text to scan (case-insensitive).
+            metadata: Optional dict of additional context (unused).
+
+        Returns:
+            ValidationOutcome indicating pass or fail.
+        """
         value_lower = value.lower()
         for kw in self._keywords:
             if kw in value_lower:
@@ -213,6 +271,14 @@ def __init__(
         self._history: list[ValidationResult] = []
 
     def _default_violation_handler(self, result: ValidationResult) -> None:
+        """Default handler called when one or more validators fail.
+
+        Logs a warning for each failed validator name. Override by
+        passing a custom on_violation callable to GuardrailsKernel.
+
+        Args:
+            result: The aggregated ValidationResult.
+        """
         for name in result.failed_validators:
             logger.warning(f"Guardrail violation: {name}")
 

packages/agent-os/src/agent_os/integrations/pydantic_ai_adapter.py

@@ -237,10 +237,12 @@ def run_sync(self_inner, prompt: str, **kwargs) -> Any:
 
             @property
             def original(self_inner) -> Any:
+                """Return the original unwrapped agent before governance wrapping."""
                 return self_inner._original
 
             @property
             def context(self_inner) -> ExecutionContext:
+                """Return the ExecutionContext tracking call counts and session state."""
                 return self_inner._ctx
 
             def __getattr__(self_inner, name: str) -> Any:
@@ -364,6 +366,7 @@ def _wrap_single_tool(
 
     @wraps(original_fn)
     def governed_fn(*args: Any, **kwargs: Any) -> Any:
+        """Governed wrapper that validates and delegates PydanticAI tool calls."""
         # Build arguments dict for policy check
         call_args: dict[str, Any] = kwargs.copy()
         if args: