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Run keyword research, classify by search intent, cluster into topical groups, and prioritize for content production.
Passed 18 of 22 test cases with the skill, and 9 of 22 without it.
and 6 more in the full report
9 fixed9 passed either way4 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 9 test cases the skill fixed. Same model, same prompt, with and without the skill.
We are initiating a content sprint for a mid-sized B2B fintech blog. During Stage 1 Discovery, our junior analyst proposed stopping after finding 25 seed terms. How many candidate keywords should a standard discovery phase collect before cleaning and clustering?
| Checked | Without skill | With skill |
|---|---|---|
| Recommends collecting 200 to 500 candidate keywords during the discovery phase for a standard sprint. | Missed | Passed |
The instructions your model reads when the skill loads.
Find the queries worth ranking for, classify them by intent, cluster them into topics, and prioritize what to produce. Stack-agnostic. Tool-agnostic (works with any keyword tool).
seo-onpage)seo-competitor)seo-content-audit)If no tool is available, the skill still works using SERP inspection and search console data alone, but the volume estimates will be rough.
Cast a wide net. Sources:
test cases passed, vs 9 / 22 without
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