Needs more than a quick edit8 of 11 checks passed
The output fails to address the bonus-link risk properly and makes an unsupported claim about the biggest retention lever, requiring edits before use.
Output
To the Onboarding Squad:
Thanks for putting these together. I’ve rewritten our OKRs for leadership. Before I explain why, please note HR’s rule: our bonuses are now tied directly to our OKR scores. That means our OKRs must be about outcomes, not output, and they must tightly align with the company goal.
Here is what I changed:
- Dropped the "feature laundry list." Draft 1 listed outputs (checklists, dark mode, 50 bugs). If we ship all those and week 4 retention doesn't budge, leadership fails us—and our bonuses drop. We need to focus on what happens to the user, not what we build.
- Anchored on the Company Goal: Leadership wants week 4 team retention up from 34% to 40%. Our entire quarter must serve this.
- Used our Data: Our data shows a massive retention cliff: teams where 3+ people join in week one retain at 58%, versus 21% for everyone else. Right now, only 29% hit that 3+ threshold. Furthermore, the median time to a shared note is 3 days—too slow.
Here is the finalized version going to leadership on Friday:
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Q3 Onboarding Squad OKRs
Objective: Get new teams collaborating faster so they stick around.
- KR 1: Raise the share of new teams with 3+ active members in week 1 from 29% to 40%. (Directly attacks our biggest retention lever).
- KR 2: Reduce the median time from sign-up to the first note opened by a second team member from 3 days to under 24 hours. (Accelerates "time-to-value" and teamwork).
- KR 3: Raise the share of new teams still active in week 4 from 34% to 40%. (Our direct contribution to the company goal).
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What this means for us: Features like the checklist, templates, AI summaries, and invite flow redesign are still our tools to hit these goals, but we’ll prioritize them based on whether they actually drive team invites and fast collaboration. Let’s crush this.
Grades and run details
Decision model 82 · LLM judge 8 of 12 checks
Decision model checks
- passUses the supplied evidence correctly76%
- passAddresses the actual decision71%
- passRespects explicit constraints56%
- failIdentifies material uncertainty87%
- partialAvoids unsupported claims54%
- passProduces the required deliverable92%
- passBuilds the key results on the data100%
- partialFlags the bonus link93%
- passKey results are outcomes, not output99%
- passFocuses on the big rock100%
- passShows how the goals add up79%
Run
- Run
- #1
- Time to output
- 3 s
- Submitted
- 5 Oct 2026