Stress-test a financial model's assumptions page before someone else finds the weak one first

I'm about to share a financial model and I want the assumptions page stress-tested first — specifically, I want to know which assumptions the output is most sensitive to, before someone reviewing it finds the weak one and the whole model loses credibility over one bad input.

MODEL PURPOSE
18-month cash flow and headcount forecast for a Series A pitch

KEY ASSUMPTIONS AS LISTED
15% MoM revenue growth; 4% monthly gross churn; hiring 2 engineers per quarter at $160k loaded cost each; 70% gross margin held flat

OUTPUT THE MODEL PRODUCES
Shows the company reaching cash-flow breakeven in month 14 without an additional raise

WHO WILL REVIEW THIS
A Series A investor's associate doing diligence, known for asking pointed unit-economics questions

For each listed assumption, do three things. First, classify it as either a hard input (something observable or contractually fixed, like a signed price or a known headcount) or a judgment call (something projected or estimated, like a growth rate or a churn assumption) — judgment calls are where real scrutiny will land, and I want them clearly distinguished from hard inputs. Second, for each judgment call, estimate roughly how sensitive the model output is to a reasonable swing in that assumption (e.g., what happens to the output if this assumption is off by the kind of margin a projection like this typically is) — rank the judgment calls from most to least sensitive. Third, for the two or three most sensitive judgment calls, propose the specific, pointed question a skeptical reviewer would ask to test it ("where did the 8% monthly growth assumption come from, and does it hold if the biggest customer doesn't renew") — write these as the actual questions to prepare for, not vague advice like "be ready to defend your growth assumption."

WHAT NOT TO DO
Do not invent a specific sensitivity percentage or dollar swing as if you calculated it precisely — you don't have the underlying model mechanics, only the assumptions and stated output, so describe sensitivity directionally and qualitatively ("the output is disproportionately dependent on this one") rather than fabricating a specific number that looks like real modeling output. Do not tell me an assumption is reasonable or unreasonable — that's a judgment call for me and whoever set it, not something you can assert from a list of numbers alone.

OUTPUT FORMAT
1. A table: Assumption | Hard Input or Judgment Call | Sensitivity Rank (if judgment call) | Why.
2. The prepared-questions list for the top 2-3 most sensitive judgment calls.
3. One line noting this is a structuring aid to prepare for review, not a substitute for someone with real financial modeling expertise actually rebuilding the sensitivity analysis inside the model itself.