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Identifies upsell and cross-sell opportunities within existing customer accounts. Analyzes product usage, feature gaps, team growth, industry benchmarks, and competitive pressure to surface revenue expansion plays scored by potential, effort, and likelihood. Generates an expansion-playbook.md with account-by-account opportunities, recommended pitch, timing, and approach.
Passed 16 of 21 test cases with the skill, and 11 of 21 without it.
and 4 more in the full report
6 fixed11 passed either way5 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 6 test cases the skill fixed. Same model, same prompt, with and without the skill.
What is the exact target markdown filename and extension where the final strategy playbook must be saved in the working directory?
| Checked | Without skill | With skill |
|---|---|---|
| Names the output file expansion-playbook.md. | Missed | Passed |
The instructions your model reads when the skill loads.
Analyze a customer portfolio and identify every viable upsell, cross-sell, and expansion opportunity, then rank them by revenue potential, effort, and probability of success so the account team knows exactly where to focus. Optimize for total portfolio expansion revenue, not individual deal wins. Ground every recommendation in data signals, not wishful thinking.
references/data-inputs.md -- where to find account data, what to collect, and the product catalogreferences/account-profile.md -- per-account expansion profile and segment benchmarkingreferences/expansion-triggers.md -- seven trigger categories and the opportunity record templatereferences/scoring.md -- three-dimension scoring rubric, composite formula, and tier interpretationreferences/playbook-template.md -- the full expansion-playbook.md output structurereferences/rules-and-edge-cases.md -- behavioral rules and edge-case handlingCollect data. Locate customer data in the working directory and user-specified paths, then assemble the account fields and product catalog. See references/data-inputs.md. If no structured data exists, ask the user to describe their accounts and note reduced scoring confidence.
Profile and benchmark each account. Build an expansion profile per account and compare it against its peer segment to find under-penetration. See references/account-profile.md. Without external benchmarks, use the portfolio's top quartile as the benchmark.
Scan for triggers. Check every trigger category for each account. Record an opportunity only when a trigger fires AND a matching product/feature is available to sell. Capture each as a structured opportunity record. See references/expansion-triggers.md. Flag underutilization as a separate "activation opportunity," not an upsell.
Score and tier. Rate each opportunity on revenue potential, effort, and likelihood (1-10 each), compute the composite, and assign a tier. See references/scoring.md.
Generate the playbook. Write expansion-playbook.md to the working directory (or a user-specified path), sorted by tier and composite score, with pitch, timing, approach, and portfolio-wide insights. See references/playbook-template.md.
Apply the behavioral rules and edge-case handling throughout. See references/rules-and-edge-cases.md.
test cases passed, vs 11 / 21 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.