quick fix for agent default behaviour (#136)

* quick fix for agent default behaviour

* adjust docstring and RESEARCH.md

* Fix ruff formatting in ops.py

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

---------

Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>

Author: petermuehlbacher

docs/reference/RESEARCH.md

@@ -69,7 +69,7 @@ Each row gets its own agent that researches independently.
 | `task` | str | The agent task describing what to research |
 | `session` | Session | Optional, auto-created if omitted |
 | `input` | BaseModel \| DataFrame \| UUID | Optional input context |
-| `effort_level` | EffortLevel | LOW, MEDIUM, or HIGH (default: LOW) |
+| `effort_level` | EffortLevel | LOW, MEDIUM, or HIGH (default: MEDIUM) |
 | `llm` | LLM | Optional agent LLM override |
 | `response_model` | BaseModel | Optional schema for structured output |
 | `return_table` | bool | (`single_agent` only) If True, returns a table instead of a scalar result |
@@ -78,8 +78,8 @@ Each row gets its own agent that researches independently.
 
 The effort level lets you control how thorough the research is.
 
-- `LOW`: Quick lookups, basic web searches, fast and cheap (default)
-- `MEDIUM`: More thorough research, multiple sources consulted
+- `LOW`: Just a single LLM call, not a real agent, cheapest & fastest
+- `MEDIUM`: More thorough research, multiple sources consulted (default)
 - `HIGH`: Deep research, cross-referencing sources, higher accuracy
 
 ### Response model

src/everyrow/ops.py

@@ -51,6 +51,9 @@
 InputData = UUID | list[dict[str, Any]] | dict[str, Any]
 
 
+DEFAULT_EFFORT_LEVEL = EffortLevel.MEDIUM
+
+
 class DefaultAgentResponse(BaseModel):
     answer: str
 
@@ -141,7 +144,7 @@ async def single_agent[T: BaseModel](
     task: str,
     session: Session | None = None,
     input: BaseModel | UUID | Result | None = None,
-    effort_level: EffortLevel | None = EffortLevel.LOW,
+    effort_level: EffortLevel | None = DEFAULT_EFFORT_LEVEL,
     llm: LLM | None = None,
     iteration_budget: int | None = None,
     include_research: bool | None = None,
@@ -155,7 +158,7 @@ async def single_agent(
     task: str,
     session: Session | None = None,
     input: BaseModel | UUID | Result | None = None,
-    effort_level: EffortLevel | None = EffortLevel.LOW,
+    effort_level: EffortLevel | None = DEFAULT_EFFORT_LEVEL,
     llm: LLM | None = None,
     iteration_budget: int | None = None,
     include_research: bool | None = None,
@@ -168,7 +171,7 @@ async def single_agent[T: BaseModel](
     task: str,
     session: Session | None = None,
     input: BaseModel | DataFrame | UUID | Result | None = None,
-    effort_level: EffortLevel | None = EffortLevel.LOW,
+    effort_level: EffortLevel | None = DEFAULT_EFFORT_LEVEL,
     llm: LLM | None = None,
     iteration_budget: int | None = None,
     include_research: bool | None = None,
@@ -182,7 +185,7 @@ async def single_agent[T: BaseModel](
         session: Optional session. If not provided, one will be created automatically.
         input: Input data (BaseModel, DataFrame, UUID, or Result).
         effort_level: Effort level preset (low/medium/high). Mutually exclusive with
-            custom params (llm, iteration_budget, include_research). Default: low.
+            custom params (llm, iteration_budget, include_research). Default: medium.
         llm: LLM to use. Required when effort_level is None.
         iteration_budget: Number of agent iterations (0-20). Required when effort_level is None.
         include_research: Include research notes. Required when effort_level is None.
@@ -224,7 +227,7 @@ async def single_agent_async[T: BaseModel](
     task: str,
     session: Session,
     input: BaseModel | DataFrame | UUID | Result | None = None,
-    effort_level: EffortLevel | None = EffortLevel.LOW,
+    effort_level: EffortLevel | None = DEFAULT_EFFORT_LEVEL,
     llm: LLM | None = None,
     iteration_budget: int | None = None,
     include_research: bool | None = None,
@@ -272,7 +275,7 @@ async def agent_map(
     task: str,
     session: Session | None = None,
     input: DataFrame | UUID | TableResult | None = None,
-    effort_level: EffortLevel | None = EffortLevel.LOW,
+    effort_level: EffortLevel | None = DEFAULT_EFFORT_LEVEL,
     llm: LLM | None = None,
     iteration_budget: int | None = None,
     include_research: bool | None = None,
@@ -335,7 +338,7 @@ async def agent_map_async(
     task: str,
     session: Session,
     input: DataFrame | UUID | TableResult,
-    effort_level: EffortLevel | None = EffortLevel.LOW,
+    effort_level: EffortLevel | None = DEFAULT_EFFORT_LEVEL,
     llm: LLM | None = None,
     iteration_budget: int | None = None,
     include_research: bool | None = None,