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Get Started Free →Structured PM 1:1 templates by partner type — manager, engineering-manager partner, designer, IC reports, cross-functional — grounded in Radical Candor, the GROW coaching model, and the Manager Tools 1:1 framework.
.claude/skills/borghei-pm-1on1s/SKILL.md| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-03 | ✗→✓ | ▲ Improved | -23% | 0% |
| case-04 | ✗→✓ | ▲ Improved | 108% | 0% |
| case-07 | ✗→✓ | ▲ Improved | 129% | 0% |
| case-09 | ✗→✓ | ▲ Improved | 86% | 0% |
| case-10 | ✗→✓ | ▲ Improved | 90% | 0% |
PMs run more 1:1s than almost any other role: with their manager, their engineering manager partner, their design lead, cross-functional partners (sales, support, data), and -- once they have reports -- with their direct PMs. Each 1:1 type has a different purpose, cadence, and ideal structure.
This skill provides templates and question banks for the most common 1:1 types a PM runs, calibrated to the PM context. It draws on Kim Scott's Radical Candor (caring personally + challenging directly), the GROW coaching model (Whitmore), the Manager Tools 1:1 framework (Auzenne & Horstman), and PM-specific 1:1 patterns popularized by senior product leaders.
pm-onboarding/ for those.Before drafting the 1:1 agenda, confirm these inputs. If any is unknown or vague, ASK — do not assume:
Stop rule: ask only the 2-3 that most change the output. If the user says "just draft it," proceed and list your assumptions at the top of the artifact.
Load the reference that matches the task; keep this file lean and pull detail on demand.
assets/kickoff_template.md — script for kicking off a new 1:1 relationship.assets/1on1_notes_template.md — recurring 1:1 notes template.assets/manager_1on1_agenda.md — ready-to-use agenda for your manager 1:1.External: Scott, K. Radical Candor (2017); Whitmore, J. Coaching for Performance (GROW); Auzenne & Horstman, The Effective Manager (Manager Tools 1:1).
In Scope: 1:1 templates for the 5 common PM partner types; the GROW coaching framework for direct reports; Radical Candor feedback; kickoff conversation script; notes/agenda templates.
Out of Scope: Formal performance management (PIP, terminations, reviews — requires HR); compensation conversations; skip-level design from the senior-leader perspective; career conversations beyond growth-plan refresh (use pm-career-ladder/).
Caveats: 1:1 patterns are culturally inflected — calibrate directness to the room. Templates are starting points that should evolve as the relationship deepens. Re-establish the kickoff conversation when you join a new team.
| Integration | Direction | What Flows | |-------------|-----------|------------| | pm-career-ladder/ | Bidirectional | Quarterly growth 1:1s use the ladder rubric as the calibration tool | | pm-onboarding/ | Receives from | Onboarding 1:1s evolve into steady-state 1:1s after day 90 | | pm-interview-prep/ | Reuses | Behavioral story prep often surfaces from 1:1 reflections | | senior-pm/stakeholder-mapper/ | Reuses | Tier-1 stakeholders should be your weekly 1:1s | | personal-productivity/weekly-review/ | Feeds into | Weekly review captures 1:1 actions and growth-plan progress |
| Case | Status | Duration (ms) | Turns | Tokens | Tool calls | ||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Without | With | Δ | Without | With | Δ | Without | With | Δ | Without | With | Δ | ||
case-01 | fail→fail | 15,739 | 10,797 | -31% | 1 | 1 | 0% | 2,166 | 2,762 | +28% | 0 | 0 | — |
case-02 | fail→fail | 17,299 | 14,785 | -15% | 1 | 1 | 0% | 2,463 | 3,305 | +34% | 0 | 0 | — |
case-03 | fail→pass | 16,050 | 5,091 | -68% | 1 | 1 | 0% | 2,663 | 2,046 | -23% | 0 | 0 | — |
case-04 | fail→pass | 17,766 | 28,589 | +61% | 1 | 1 | 0% | 2,607 | 5,426 | +108% | 0 | 0 | — |
case-05 | fail→fail | 26,124 | 28,997 | +11% | 1 | 1 | 0% | 3,860 | 5,471 | +42% | 0 | 0 | — |
case-06 | fail→fail | 16,649 | 19,836 | +19% | 1 | 1 | 0% | 2,590 | 4,334 | +67% | 0 | 0 | — |
case-07 | fail→pass | 9,107 | 11,562 | +27% | 1 | 1 | 0% | 1,284 | 2,938 | +129% | 0 | 0 | — |
case-08 | pass→pass | 13,587 | 13,620 | +0% | 1 | 1 | 0% | 2,068 | 3,219 | +56% | 0 | 0 | — |
case-09 | fail→pass | 10,928 | 13,794 | +26% | 1 | 1 | 0% | 1,780 | 3,316 | +86% | 0 | 0 | — |
case-10 | fail→pass | 11,001 | 12,544 | +14% | 1 | 1 | 0% | 1,648 | 3,125 | +90% | 0 | 0 | — |
case-11 | pass→pass | 14,136 | 16,535 | +17% | 1 | 1 | 0% | 2,095 | 3,708 | +77% | 0 | 0 | — |
case-12 | fail→pass | 14,091 | 15,170 | +8% | 1 | 1 | 0% | 2,065 | 3,654 | +77% | 0 | 0 | — |
case-13 | pass→pass | 12,825 | 15,605 | +22% | 1 | 1 | 0% | 1,844 | 3,593 | +95% | 0 | 0 | — |
case-14 | fail→pass | 10,949 | 13,124 | +20% | 1 | 1 | 0% | 1,551 | 3,055 | +97% | 0 | 0 | — |
case-21 | pass→pass | 12,744 | 11,639 | -9% | 1 | 1 | 0% | 1,874 | 3,013 | +61% | 0 | 0 | — |
case-15 | pass→pass | 13,875 | 15,864 | +14% | 1 | 1 | 0% | 2,050 | 3,547 | +73% | 0 | 0 | — |
case-16 | fail→fail | 11,194 | 11,783 | +5% | 1 | 1 | 0% | 1,617 | 2,941 | +82% | 0 | 0 | — |
case-17 | pass→pass | 12,787 | 15,080 | +18% | 1 | 1 | 0% | 2,049 | 3,647 | +78% | 0 | 0 | — |
case-18 | pass→pass | 12,611 | 9,134 | -28% | 1 | 1 | 0% | 1,803 | 2,626 | +46% | 0 | 0 | — |
case-19 | pass→pass | 12,606 | 10,694 | -15% | 1 | 1 | 0% | 1,946 | 2,806 | +44% | 0 | 0 | — |
case-20 | fail→fail | 15,547 | 14,016 | -10% | 1 | 1 | 0% | 2,296 | 3,350 | +46% | 0 | 0 | — |
case-22 | pass→pass | 15,512 | 13,003 | -16% | 1 | 1 | 0% | 2,271 | 3,189 | +40% | 0 | 0 | — |
case-23 | fail→pass | 9,697 | 11,269 | +16% | 1 | 1 | 0% | 1,357 | 2,898 | +114% | 0 | 0 | — |
case-24 | fail→pass | 15,800 | 15,808 | +0% | 1 | 1 | 0% | 2,327 | 3,505 | +51% | 0 | 0 | — |
case-25 | pass→pass | 8,646 | 11,867 | +37% | 1 | 1 | 0% | 1,345 | 2,936 | +118% | 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. 25 cases were attempted. The headline lift of +36 percentage points is the difference between those two pass rates over the 25 comparable cases.
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.