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Run a full Jobs-To-Be-Done discovery workshop with switch interviews, forces-of-progress mapping, ODI outcome scoring, and opportunity statements across 2hr, 4hr, and 8hr formats.
Passed 20 of 25 test cases with the skill, and 14 of 25 without it.
and 4 more in the full report
7 fixed13 passed either way4 still failing1 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 7 test cases the skill fixed. Same model, same prompt, with and without the skill.
When mapping customer switching behavior for our fintech app, my team combined the current solution's habits and the new solution's anxieties into a single bucket called 'User Hesitations'. Is this structural approach correct according to switching theory?
| Checked | Without skill | With skill |
|---|---|---|
| rejects combining habits and anxieties into a single friction category | Missed | Passed |
| identifies habit of the present and anxiety of the new as distinct forces opposing change | Passed | Passed |
The instructions your model reads when the skill loads.
Run a Jobs-To-Be-Done (JTBD) workshop end-to-end. This skill is the workshop facilitation companion to the execution/job-stories/ skill (the writing format for backlog stories). Where job-stories/ produces When/Want/So statements for individual backlog items, this skill produces the upstream discovery output -- the job hierarchy, the forces driving switching behavior, and the desired-outcome statements that anchor product strategy.
The workshop synthesizes four JTBD schools: Christensen's milkshake hiring frame, Ulwick's Outcome-Driven Innovation (ODI) with importance/satisfaction scoring, Klement's situation-motivation-outcome canvas (the job story format), and Moesta's switch interview method surfacing the four forces of progress (push, pull, anxiety, habit). A well-run workshop produces three artifacts: a ranked job hierarchy with measurable outcome statements, a forces-of-progress map, and a prioritized opportunity list ready to feed PRDs, OKRs, or roadmap themes.
Before planning the workshop, 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.
test cases passed, vs 14 / 25 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.