workflow

tests/test_workflow_skill_exec.py

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+from __future__ import annotations
+
+import pytest
+
+from skills_learning.models import FlowStep, FlowTemplateSkill, SkillMetadata
+from workflow.skill_exec import (
+    SkillExecutionError,
+    resolve_skill_steps,
+    run_flow_template_skill,
+)
+
+
+def _skill() -> FlowTemplateSkill:
+    return FlowTemplateSkill(
+        metadata=SkillMetadata(
+            name="send message",
+            description="Send a message",
+            kind="flow_template",
+        ),
+        steps=[
+            FlowStep("input_text", {"text": "{message}"}),
+            FlowStep("tap", {"x": 1, "y": 2}),
+        ],
+        parameters={"message": {"type": "string"}},
+    )
+
+
+def test_resolve_skill_steps_substitutes_valid_args() -> None:
+    resolved = resolve_skill_steps(_skill(), {"message": "hello"})
+
+    assert resolved == [
+        {"tool_name": "input_text", "args": {"text": "hello"}},
+        {"tool_name": "tap", "args": {"x": 1, "y": 2}},
+    ]
+
+
+def test_missing_required_parameter_fails_before_tool_call() -> None:
+    calls: list[str] = []
+
+    with pytest.raises(SkillExecutionError, match="missing required"):
+        run_flow_template_skill(
+            _skill(),
+            {},
+            tools={"input_text": lambda **kwargs: calls.append("input_text")},
+        )
+
+    assert calls == []
+
+
+def test_non_flow_template_skill_is_rejected() -> None:
+    skill = FlowTemplateSkill(
+        metadata=SkillMetadata(
+            name="knowledge",
+            description="Not executable",
+            kind="knowledge",
+        )
+    )
+
+    with pytest.raises(SkillExecutionError, match="flow_template"):
+        resolve_skill_steps(skill, {})
+
+
+def test_run_flow_template_skill_dispatches_resolved_tools() -> None:
+    calls: list[tuple[str, dict[str, object]]] = []
+
+    results = run_flow_template_skill(
+        _skill(),
+        {"message": "hello"},
+        tools={
+            "input_text": lambda **kwargs: calls.append(("input_text", kwargs)) or {"ok": True},
+            "tap": lambda **kwargs: calls.append(("tap", kwargs)) or {"ok": True},
+        },
+    )
+
+    assert [result.success for result in results] == [True, True]
+    assert calls == [
+        ("input_text", {"text": "hello"}),
+        ("tap", {"x": 1, "y": 2}),
+    ]