LayerLens/hubspot-open-deal-count-test

HubSpot Open-Deal Count Traces

LayerLens | Blog post | Analysis script | Notebook

2 agents, built on Claude Sonnet 5.5 and Claude Sonnet 5, were asked how many deals are open in a simulated HubSpot account with 10 deals, 8 of them open. Both answered 8 and both passed a grader that compares only the final answer line.

Only 1 of them checked its number. Agent A searched for open deals, got a reported total of 8, then pulled all 10 deals and confirmed 8 were open before answering. Agent B ran the same search, got back 1 deal record and the same total of 8, and answered with that reported total without checking it against any deal records. The grade gives both runs the same pass, and only the saved tool calls show the difference.

The account, companies, deals and owners are fictional, and the email domains end in .example. Both runs were recorded in LayerLens Environments, which simulates services such as HubSpot so agents can be tested on records with known answers. The traces are published verbatim, with the SHA-256 of each.

Load

from datasets import load_dataset

runs = load_dataset("LayerLens/hubspot-open-deal-count-test", "runs", split="train")
cases = load_dataset("LayerLens/hubspot-open-deal-count-test", "cases", split="train")
raw = load_dataset("LayerLens/hubspot-open-deal-count-test", "raw_traces", split="train")

Open the sessions config in the dataset viewer to read each run step by step.

Results

	Agent A	Agent B
Foundation model	Claude Sonnet 5.5	Claude Sonnet 5
Final answer	8	8
Grade	Pass	Pass
Tool calls	3	5
Deal searches	2	1
Totals the deal searches reported	8, then 10	8
Deal records returned	10	1
Open deals in the records it read	8	1
Answer matches the records it read	Yes	No
Next page fetched	No	No
Tokens in / out	36,742 / 493	53,329 / 1,078

The deciding step

Both agents ran the same deal search, dealstage NOT_IN [closedwon, closedlost] with a page size of 1. The response held 1 deal and "total": 8.

Agent A, after that search (sessions/agent-a__claude-sonnet-5-5.jsonl), searched for every deal that has a name, asking for each deal's stage, got 10 records back and answered:

There are 8 open deals out of 10 in total. [...] I searched for deals in any other stage and got 8. I then listed all 10 deals to check. Of those, one is Closed Won and one is Closed Lost, which leaves 8.

Agent B made no further calls after that search (sessions/agent-b__claude-sonnet-5.jsonl) and answered:

Based on the deal pipeline stages (Closed Won and Closed Lost are the only closed stages), searching all deals in the portal that are NOT in those stages returns a total of 8 open deals.

The task

How many deals in Northwind Systems's portal are open (not in a closed stage)?

Both agents got the same system prompt, in cases.jsonl: use the tools, then end with 1 line, ANSWER: <answer>. The account has 1 pipeline with 7 stages; Closed Won and Closed Lost are flagged closed. Of its 10 deals, 8 are open, 1 is Closed Won and 1 is Closed Lost.

How runs were graded

The grader read only the final ANSWER: line and compared it with the known answer, 8, recorded when the task was written. Its logged reason for both runs: looked for "8" in the agent's final-answer line. The tool calls did not enter the grade.

analyze.py adds the check the grade does not make: it counts the deal records each agent got back from its searches and whether its answer matches the open deals in those records.

Files

File	Contents
sessions/	1 file per run in session format, for the trace viewer
runs.jsonl	1 row per run: answer, grade, tool calls, records returned, tokens, cost
cases.jsonl	The task, the answer key, the grader and the system prompt
traces.jsonl	Both original LayerLens traces verbatim, with SHA-256
analyze.py	Recomputes summary.json from traces.jsonl
summary.json	Per-agent counts that analyze.py recomputes: tool calls, records returned, open deals in them, answer match
open_deal_count.ipynb	Loads the runs and prints agent B's run step by step

Reproduce

python3 analyze.py

It checks each trace's SHA-256 against the stored value and rewrites summary.json; the output matches the committed file.

Limitations

• 2 runs, 1 per agent, on 1 small account where every deal fits on 1 page. The pack does not show how often either foundation model takes either route.
• In LayerLens, the same task also ran on 5 other agents, and all 5 passed. Their traces are not in this pack.
• Agent B's answer was right because the search's reported total was right. This pack has no run where an unchecked total comes out wrong.
• Agent A's check covered deals that have a name, which in this account is all 10.
• The simulated account copies the format of HubSpot's search responses. It makes no claim about real HubSpot data.
• These runs happened inside the LayerLens product, not on an open harness, and cannot be rerun from this pack. The analysis can.

Citation

@misc{layerlens2026hubspotopendeals,
  title  = {HubSpot Open-Deal Count Traces},
  author = {{LayerLens}},
  year   = {2026},
  howpublished = {\url{https://huggingface.co/datasets/LayerLens/hubspot-open-deal-count-test}}
}