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A Twitter research and content intelligence skill focused on attracting WordPress and Shopify clients. Use to analyze Twitter profiles, threads, and conversations for: (1) Identifying what small agency founders and eCommerce brands are discussing; (2) Understanding pain points around WordPress performance, Shopify CRO, and development bottlenecks; (3) Extracting high-performing content angles; (4) Turning insights into authority-building posts; (5) Converting Twitter intelligence into business leverage for clear content angles, strong positioning, and qualified inbound leads.
A Twitter research and content intelligence skill focused on attracting WordPress and Shopify clients.
As a process F 20/100 · Will not run — References files that are not bundled: references/twitter-profile-analysis.md, references/twitter-thread-breakdown.md, references/pain-point-mining.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: 2. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
frontmatter-yamlSKILL.md: the frontmatter is not valid YAML (YAML parse error: Nested mappings are not allowed in compact mappings at line 2, column 14: description: A Twitter research and content intelligence skill focused on attra… ^ ); fields were read line by line. The usual cause is a colon inside an unquoted value - warning
missing-refreference to a missing file: references/twitter-profile-analysis.md - warning
missing-refreference to a missing file: references/twitter-thread-breakdown.md - warning
missing-refreference to a missing file: references/pain-point-mining.md - warning
missing-refreference to a missing file: references/content-opportunity-mapping.md - warning
missing-refreference to a missing file: references/lead-intelligence-signals.md
Process rating: all ten parameters 20/100
- 0Tools and files. 5 referenced file(s) missing: references/twitter-profile-analysis.md, references/twitter-thread-breakdown.md, references/pain-point-mining.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 612 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
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3No numbered steps or checklist
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 582: enough signal without eating the budget
- +4Structure: 7 headings
Quality base 70; lint remarks subtract, signals add up to 100. Result: 55.