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Get Started Free →Design a structured onboarding experience that gets new team members productive in 30, 60, and 90 days. Use when a new hire is joining, when contractors or agency partners need to ramp up, when an existing team is restructuring and members are switching focus, or when current onboarding feels chaotic and slow. Also triggers when one person owns all the tribal knowledge and you need to capture it, when you keep losing people in their first 90 days, or when a new project has many fresh members joi
.claude/skills/rampstackco-team-onboarding-playbook/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-05 | ✗→✓ | ▲ Improved | 109% | 0% |
| case-11 | ✗→✓ | ▲ Improved | 88% | 0% |
| case-13 | ✗→✓ | ▲ Improved | 81% | 0% |
| case-14 | ✗→✓ | ▲ Improved | 76% | 0% |
| case-17 | ✗→✓ | ▲ Improved | 115% | 0% |
A repeatable framework for building an onboarding playbook that ramps new team members predictably without burning out the people training them.
documentation-strategy).A good onboarding plan operates on 4 layers. Build all four.
The first week is mostly about belonging, not productivity. Get this right and everything else accelerates.
The next phase is context. The new person needs to understand the system before they can change it.
A reading list is part of this. Keep it short. Annotated. Curated.
By week 2 or 3, the new person should be making real contributions. Not because they are fully ramped, but because contribution is how ramping happens.
The first task matters. Pick something that touches the main systems but cannot break anything important. Something that ships gives confidence and visibility.
By the end of 90 days, the new person should be a full member of the team.
90 days is a checkpoint, not a finish line. Document what worked and what was missing for the next person.
Every onboarding plan should have explicit milestones at 30, 60, and 90 days.
If someone is significantly behind these markers at the 30/60/90 checkpoints, address it directly. Either the plan is wrong, the support is wrong, or the role fit is wrong. Hoping it resolves itself does not work.
The framework above applies to every role. The specifics differ.
Adapt to your role and stack. The shape stays the same.
Deliverables:
references/onboarding-checklist.md: A day-by-day, week-by-week checklist for the first 30 days, with role-specific variants and a 30/60/90 review template.| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 24,765 | 35,894 | +45% | 1 | 1 | 0% | 4,310 | 8,339 | +93% | 0 | 0 | — |
case-02 | pass→pass | 18,187 | 19,331 | +6% | 1 | 1 | 0% | 2,922 | 5,104 | +75% | 0 | 0 | — |
case-03 | pass→pass | 17,711 | 27,659 | +56% | 1 | 1 | 0% | 2,983 | 6,837 | +129% | 0 | 0 | — |
case-04 | pass→pass | 19,615 | 26,948 | +37% | 1 | 1 | 0% | 3,365 | 6,704 | +99% | 0 | 0 | — |
case-05 | fail→pass | 12,385 | 11,690 | -6% | 1 | 1 | 0% | 1,906 | 3,985 | +109% | 0 | 0 | — |
case-06 | fail→fail | 15,090 | 16,978 | +13% | 1 | 1 | 0% | 2,509 | 4,893 | +95% | 0 | 0 | — |
case-07 | fail→fail | 16,039 | 15,985 | -0% | 1 | 1 | 0% | 2,564 | 4,664 | +82% | 0 | 0 | — |
case-08 | pass→pass | 14,227 | 14,213 | -0% | 1 | 1 | 0% | 2,340 | 4,416 | +89% | 0 | 0 | — |
case-09 | pass→pass | 12,081 | 10,576 | -12% | 1 | 1 | 0% | 2,068 | 3,945 | +91% | 0 | 0 | — |
case-10 | pass→pass | 14,872 | 8,694 | -42% | 1 | 1 | 0% | 2,377 | 3,484 | +47% | 0 | 0 | — |
case-11 | fail→pass | 15,582 | 16,537 | +6% | 1 | 1 | 0% | 2,514 | 4,718 | +88% | 0 | 0 | — |
case-12 | fail→fail | 14,376 | 14,843 | +3% | 1 | 1 | 0% | 2,114 | 4,411 | +109% | 0 | 0 | — |
case-13 | fail→pass | 12,775 | 12,142 | -5% | 1 | 1 | 0% | 2,250 | 4,074 | +81% | 0 | 0 | — |
case-14 | fail→pass | 10,975 | 6,782 | -38% | 1 | 1 | 0% | 1,809 | 3,178 | +76% | 0 | 0 | — |
case-15 | pass→pass | 15,107 | 13,214 | -13% | 1 | 1 | 0% | 2,182 | 4,104 | +88% | 0 | 0 | — |
case-16 | pass→pass | 9,269 | 6,246 | -33% | 1 | 1 | 0% | 1,208 | 2,987 | +147% | 0 | 0 | — |
case-17 | fail→pass | 14,400 | 15,446 | +7% | 1 | 1 | 0% | 2,053 | 4,411 | +115% | 0 | 0 | — |
case-18 | pass→pass | 12,198 | 9,794 | -20% | 1 | 1 | 0% | 1,732 | 3,497 | +102% | 0 | 0 | — |
case-19 | fail→fail | 13,477 | 10,771 | -20% | 1 | 1 | 0% | 2,140 | 3,825 | +79% | 0 | 0 | — |
case-20 | pass→pass | 11,476 | 7,992 | -30% | 1 | 1 | 0% | 1,710 | 3,247 | +90% | 0 | 0 | — |
case-21 | pass→pass | 14,676 | 17,941 | +22% | 1 | 1 | 0% | 2,163 | 4,574 | +111% | 0 | 0 | — |
case-22 | pass→pass | 16,789 | 16,318 | -3% | 1 | 1 | 0% | 2,588 | 4,479 | +73% | 0 | 0 | — |
DecimalAI ran this skill against gemini-3.6-flash twice over the same eval suite — once with the skill loaded and once without — and compared the two runs case by case. 22 cases were attempted. The headline lift of +23 percentage points is the difference between those two pass rates over the 22 comparable cases. 2 cases got worse with the skill loaded, and they are included in that figure.
Without the skill loaded, the model failed this case. With it loaded, the same prompt on the same model passed. This is one improved case from the latest verified run; every case, including any that regressed, is in the table above.
Other measured skills in the registry, with their headline benchmark lift.