CF keyword-research
Discover, analyze, and prioritize keywords for SEO and GEO content strategies from a seed keyword or niche. Identifies high-value opportunities based on search volume, competition, intent, and business relevance. Generates topic clusters. For building a dated editorial calendar from your own Search Console data, use `content-planner` instead — this skill is seed-driven keyword discovery, not calendar scheduling. Use when asked to "find keywords", "keyword research", "keyword analysis", "search volume", "keyword difficulty", "content ideas from a seed", or any keyword discovery task.
Discover, analyze, and prioritize keywords for SEO and GEO content strategies from a seed keyword or niche.
As a process F 20/100 · No process to follow — References files that are not bundled: ../../seo/keyword-research/WORKFLOW.md
How to improve
- The text references files that are not there: add them or drop the references.
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 1. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: ../../seo/keyword-research/WORKFLOW.md
Process rating: all ten parameters 20/100
- 0Tools and files. 1 referenced file(s) missing: ../../seo/keyword-research/WORKFLOW.md
- 0Steps. Prose only: no discrete steps
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Failures and branches. Linear process with no failure handling
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 65 tokens
- 100Running it twice. No mutating operations
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +4Description does not say when NOT to use the skill (false activations)
- +4Structure: 1 headings, hard to scan
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- -15SKILL.md body under 300 characters: nearly empty
- +1No license
- +2Single-language instructions
- +5Description quotes 6 example trigger phrases
- +3Description length 589: enough signal without eating the budget
Quality base 70; lint remarks subtract, signals add up to 100. Result: 57.