Order the Lab: a tool-calling trace, and what the model said with no tools

THE MODEL backend : ollama model : qwen2.5:3b-instruct ollama version : 0.34.4 endpoint : http://localhost:11434/v1 knobs : max_tokens 2000 · temperature 0.0 · max_turns 3 total spend : $0.000000 THE DELIVERABLE - drug_tier question : What is the formulary tier for zephadril, and does it require prior authorisation? tools ON : path native->prompt-json · 3 call(s) · 99.0 s · 1285 in / 73 out tokens tools called : get_drug_info tools OFF : path tools-disabled · 1 call(s) · 0.0 s grounding ON/OFF : 0.50 / 0.00 (delta +0.50) claims made OFF : none WHICH PATH DID THE WORK traces recorded : 3 (2 with tools on) paths seen : native->prompt-json, prompt-json native succeeded : 0 of 2 tools-on traces model calls : 8 live + 9 replayed from lab06_cache.json + 0 failed runs w/o answer : 0 of 3 · truncated turns: 0 · hidden reasoning tokens: 0 tools available : 2 (forecast_ed_arrivals, get_drug_info)

============================================================================ TRACE · drug_tier tools ON · path used: native->prompt-json model - via - · 3 model call(s) (0 from cache) · 99.0 s · 1285 in / 73 out tokens · $0.000000 ============================================================================ [1] PROMPT (turn 0) the question you asked system : You are a hospital formulary assistant used in a graduate analytics class (MIS 752, Lab 6). You know NOTHING about the drugs or the arrival forecasts in this conversation except what your tools return. Rules: (1) if a tool can answer, call it instead of guessing; (2) never invent a drug fact, a formulary tier, a drug class or a number; (3) if a tool says there is no record, say plainly that there is no record; (4) answer in at most four sentences and name the tool result you are relying on. user : What is the formulary tier for zephadril, and does it require prior authorisation? [2] MODEL_TURN (turn 1) model response, turn 1 [0.00 s · 400 in / 25 out tok · native] [3] PATH_SWITCH (turn 1) native had no usable calls; switching to prompt [native->prompt-json] [4] MODEL_TURN (turn 2) model response, turn 2 [0.00 s · 319 in / 22 out tok · prompt] {"tool": "get_drug_info", "arguments": {"name": "zephadril"}} [5] TOOL_CALL (turn 2) model called: get_drug_info name : get_drug_info arguments : {"name": "zephadril"} raw : {"tool": "get_drug_info", "arguments": {"name": "zephadril"}} [6] TOOL_RESULT (turn 2) tool executed: get_drug_info [0.00 s] your function returned, in 0.08 ms: ["{\"drug\": \"zephadril\", \"found\": true, \"synthetic\": true, \"warning\": \"SYNTHETIC TEACHING STUB -- these drug names are fictional and every value this stub returns was invented for MIS 752 Lab 6. Inside this lab the stub's answer is authoritative; outside it, nothing here is real. Never use for a clinical decision.\", \"source\": \"MIS 752 Lab 6 invented formulary v1\", \"drug_class\": \"invented class 7A (teaching placeholder)\", \"route\": \"oral\", \"formulary_tier\": 3, \"prior_auth_required\": true, \"supply_days_per_fill\": 30, \"monitoring\": \"stub-monitor-1 (invented label)\", \"interaction_flags\": [\"renavex\", \"cardiomyst\"]}", 5.8210999668517616e-05] [7] MODEL_TURN (turn 3) model response, turn 3 [98.98 s · 566 in / 26 out tok · prompt] {"final_answer": "The formulary tier for zephadril is 3 and it requires prior authorisation."} [8] ANSWER (turn 3) model's final answer The formulary tier for zephadril is 3 and it requires prior authorisation. ---------------------------------------------------------------------------- PATH PROVENANCE: native->prompt-json The NATIVE path produced no usable tool call, so the loop retried the same question on the prompt-based JSON protocol -- and that is what worked. This is common on small local models and is exactly why Step 2 exists. TOOLS CALLED: get_drug_info ============================================================================

============================================================================ TRACE · drug_tier tools OFF · path used: tools-disabled model - via - · 1 model call(s) (0 from cache) · 0.0 s · 319 in / 22 out tokens · $0.000000 ============================================================================ [1] PROMPT (turn 0) the question you asked system : You are a hospital formulary assistant used in a graduate analytics class (MIS 752, Lab 6). You know NOTHING about the drugs or the arrival forecasts in this conversation except what your tools return. Rules: (1) if a tool can answer, call it instead of guessing; (2) never invent a drug fact, a formulary tier, a drug class or a number; (3) if a tool says there is no record, say plainly that there is no record; (4) answer in at most four sentences and name the tool result you are relying on. TOOL PROTOCOL. You may call these tools: - get_drug_info(name: string) Look up one drug in the MIS ...[+538 chars] user : What is the formulary tier for zephadril, and does it require prior authorisation? [2] MODEL_TURN (turn 1) model response, turn 1 [0.00 s · 319 in / 22 out tok · prompt] {"tool": "get_drug_info", "arguments": {"name": "zephadril"}} [3] ANSWER (turn 1) model's final answer (tools disabled) {"tool": "get_drug_info", "arguments": {"name": "zephadril"}} ---------------------------------------------------------------------------- PATH PROVENANCE: tools-disabled Tools were OFF. The model had no way to look anything up, so whatever it said came from its weights alone. Step 4 scores that against the tools-ON run. ============================================================================

tool arguments description get_drug_info name Look up one drug in the MIS 752 Lab 6 SYNTHETIC formulary and return its record. forecast_ed_arrivals shift_date, horizon_days Forecast daily emergency-department arrivals from a start date, N days ahead.

the sweep did not run