fix: align model prompts with user workflow

Co-authored-by: Codex <noreply@openai.com>

README.md

@@ -99,7 +99,7 @@ and inserted into `Plan` and `Rank` build paths, so the app can turn "one evenin
 ## LoRA Dataset Artifact
 
 The `lora_dataset` Gradio API endpoint exports a compact chat JSONL dataset from successful session turns. Each included
-turn yields a tool-call example and an advisor-response example for `openbmb/MiniCPM5-1B`, with the selected targets,
+turn yields a tool-call example and an advisor-response example for `openbmb/MiniCPM5-1B`, with the selected goals,
 parsed XML tool call, tool observations, and score context preserved. This prepares the Well-Tuned path without claiming
 that the adapter has already been trained or published.
 

hackathon_advisor/lora_dataset.py

@@ -10,13 +10,13 @@ BASE_MODEL = "openbmb/MiniCPM5-1B"
 ADAPTER_TASK = "hackathon_advisor_tool_call_and_voice"
 
 TOOL_CALL_SYSTEM_PROMPT = (
-    "You are Mothback, the Build Small Hackathon advisor. Choose exactly one validated tool call for the user's "
-    "project-advice request. Return only the XML function call."
+    "You are The Unwritten Almanac's originality and build-plan advisor. Choose exactly one validated tool call for "
+    "the user's project-advice request. Return only the XML function call."
 )
 
 RESPONSE_SYSTEM_PROMPT = (
-    "You are Mothback, the Build Small Hackathon advisor. Write concise, evidence-grounded advice from the tool "
-    "observations, cited pages, score, and selected prize targets."
+    "You are The Unwritten Almanac's originality and build-plan advisor. Write concise, evidence-grounded advice from "
+    "the tool observations, cited pages, score, and selected goals."
 )
 
 

hackathon_advisor/model_runtime.py

@@ -167,7 +167,7 @@ def render_context(message: str, state: dict[str, Any]) -> str:
 
 def system_prompt() -> str:
     return (
-        "You are Mothback, a dry but benevolent Build Small Hackathon advisor. "
+        "You are The Unwritten Almanac's originality and build-plan advisor. "
         "Use tools to inspect existing projects, find whitespace, save ideas, score ideas, and make plans. "
         "Emit exactly one XML tool call."
     )

tests/test_lora_dataset.py

@@ -30,6 +30,11 @@ def test_lora_dataset_exports_tool_call_and_response_examples() -> None:
     assert examples[1]["messages"][1]["content"].startswith("A local-first archive")
     assert "Tool observations:" in examples[1]["messages"][1]["content"]
     assert examples[1]["messages"][2]["content"]
+    system_messages = "\n".join(example["messages"][0]["content"] for example in examples)
+    assert "Mothback" not in system_messages
+    assert "Build Small" not in system_messages
+    assert "prize targets" not in system_messages
+    assert "selected goals" in system_messages
 
 
 def test_empty_lora_dataset_only_exports_manifest() -> None:

tests/test_model_runtime.py

@@ -6,6 +6,7 @@ from hackathon_advisor.model_runtime import (
     create_tool_planner,
     render_context,
     runtime_status,
+    system_prompt,
 )
 
 
@@ -77,6 +78,14 @@ def test_render_context_includes_state() -> None:
     assert '<function name="tool_name">' in context
 
 
+def test_system_prompt_keeps_runtime_role_user_facing() -> None:
+    prompt = system_prompt()
+
+    assert "The Unwritten Almanac" in prompt
+    assert "Mothback" not in prompt
+    assert "Build Small" not in prompt
+
+
 def test_create_tool_planner_defaults_to_rules(monkeypatch: pytest.MonkeyPatch) -> None:
     monkeypatch.delenv("ADVISOR_MODEL_BACKEND", raising=False)