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End-of-life product messaging and sunset communication framework for clear, empathetic EOL announcements that preserve customer trust.
Passed 18 of 22 test cases with the skill, and 10 of 22 without it.
and 10 more in the full report
9 fixed10 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 8 test cases the skill fixed. Same model, same prompt, with and without the skill.
We need to deprecate our legacy billing integration tier next month and move active accounts to the new subscription management platform. Please generate a full deprecation rollout framework that includes the primary announcement message, segment distribution channels, timeline recommendations, and risk monitoring steps. Ask me any missing initial details required to kick off the work.
| Checked | Without skill | With skill |
|---|---|---|
| Presents clarifying questions first before drafting the rollout framework. | Missed | Passed |
| Refrains from outputting the primary announcement message before clarifications are answered. | Missed | Passed |
The instructions your model reads when the skill loads.
Create clear, empathetic End-of-Life (EOL) communications that preserve customer trust and facilitate smooth transitions. Sunsetting a product is a high-stakes communication challenge -- done poorly, it damages brand trust and accelerates churn across your entire portfolio. Done well, it strengthens customer relationships and drives migration to replacement solutions.
The work runs in four phases: (1) Pre-announcement planning (what, why, who, when, what support, what risks), (2) Craft the message (transition narrative, customer impact, transition solution, timeline, one CTA), (3) Segment and distribute (different message and channel per segment), (4) Support and monitor (support FAQ, migration tracking, churn watch). See the playbook reference for the full framework, templates, and timeline guidance.
Before crafting the EOL communication, 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 10 / 22 without
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