changes

env/models.py

@@ -155,6 +155,7 @@ class StepResult(BaseModel):
 
 class ResetRequest(BaseModel):
     difficulty: Difficulty = Difficulty.MEDIUM
+    task: Optional[str] = None
     audio_path: Optional[str] = None
     transcript_override: Optional[str] = None
 
@@ -201,3 +202,13 @@ class PlanResponse(BaseModel):
     breakdown: Dict[str, float]
     summary: str
     final_board: str
+
+
+class TaskDescriptor(BaseModel):
+    id: str
+    name: str
+    difficulty: Difficulty
+    objective: str
+    grader: str
+    score_range: str = "[0.0, 1.0]"
+    deterministic: bool = True

env/task_catalog.py

@@ -0,0 +1,55 @@
+"""
+Explicit task catalog for validator and API task discovery.
+"""
+
+from __future__ import annotations
+
+from .models import Difficulty, TaskDescriptor
+
+
+TASK_CATALOG: list[TaskDescriptor] = [
+    TaskDescriptor(
+        id="easy",
+        name="easy",
+        difficulty=Difficulty.EASY,
+        objective=(
+            "Create the best sprint plan from a static backlog with fixed team capacity "
+            "and fixed deadlines."
+        ),
+        grader="env.graders.grade",
+    ),
+    TaskDescriptor(
+        id="medium",
+        name="medium",
+        difficulty=Difficulty.MEDIUM,
+        objective=(
+            "Revise the sprint plan after one mid-sprint disruption such as urgent work "
+            "or a developer capacity loss."
+        ),
+        grader="env.graders.grade",
+    ),
+    TaskDescriptor(
+        id="hard",
+        name="hard",
+        difficulty=Difficulty.HARD,
+        objective=(
+            "Repeatedly re-plan under multiple disruptions including added work, "
+            "capacity changes, and dependency shifts while preserving feasibility."
+        ),
+        grader="env.graders.grade",
+    ),
+]
+
+
+def get_task_catalog() -> list[TaskDescriptor]:
+    return TASK_CATALOG
+
+
+def resolve_task_name(name: str | None) -> Difficulty | None:
+    if not name:
+        return None
+    normalized = name.strip().lower()
+    for task in TASK_CATALOG:
+        if task.id == normalized or task.name == normalized:
+            return task.difficulty
+    return None

openenv.yaml

@@ -7,9 +7,27 @@ version: "1.0.0"
 entrypoint: env.environment:SprintEnv
 
 tasks:
-  - easy
-  - medium
-  - hard
+  - id: easy
+    name: easy
+    difficulty: easy
+    objective: Create the best sprint plan from a static backlog with fixed capacity and deadlines.
+    grader: env.graders.grade
+    score_range: [0.0, 1.0]
+    deterministic: true
+  - id: medium
+    name: medium
+    difficulty: medium
+    objective: Revise the sprint plan once after a single mid-sprint disruption.
+    grader: env.graders.grade
+    score_range: [0.0, 1.0]
+    deterministic: true
+  - id: hard
+    name: hard
+    difficulty: hard
+    objective: Re-plan repeatedly under multiple disruptions while preserving feasibility and value.
+    grader: env.graders.grade
+    score_range: [0.0, 1.0]
+    deterministic: true
 
 environment:
   max_steps: 20
@@ -37,6 +55,7 @@ dependencies:
 server:
   host: 0.0.0.0
   port: 7860
+  endpoint_tasks: /tasks
   endpoint_reset: /reset
   endpoint_step: /step
   endpoint_state: /state

server/app.py

@@ -23,7 +23,9 @@ from env.models import (
     ResetRequest,
     StepRequest,
     StepResult,
+    TaskDescriptor,
 )
+from env.task_catalog import get_task_catalog, resolve_task_name
 from planner import generate_plan
 
 logger = logging.getLogger(__name__)
@@ -60,13 +62,19 @@ def health():
     return {"status": "ok", "env_ready": env is not None}
 
 
+@app.get("/tasks", response_model=list[TaskDescriptor])
+def list_tasks():
+    return get_task_catalog()
+
+
 @app.post("/reset", response_model=Observation)
 def reset(request: ResetRequest = ResetRequest()):
     global env
     if env is None:
         raise HTTPException(500, "Environment not initialised")
+    requested_difficulty = resolve_task_name(request.task) or request.difficulty
     return env.reset(
-        difficulty=request.difficulty,
+        difficulty=requested_difficulty,
         audio_path=request.audio_path,
         transcript_override=request.transcript_override,
     )