CF marketing-guide
How every GooseWorks marketing playbook runs: connecting, picking the brand, where files go, the shared claims, money, research and schedule rules, and the index of what each playbook saves and who reads it. Load at the start of any playbook run. Not a marketer ask: for "what should I do first?" use where-to-start.
How every GooseWorks marketing playbook runs: connecting, picking the brand, where files go, the shared claims, money, research and schedule rules, and the…
As a process F 33/100 · No process to follow — References files that are not bundled: references/<file>.md, references/meta-levers.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: 3. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
- warning
missing-refreference to a missing file: references/<file>.md - warning
missing-refreference to a missing file: references/meta-levers.md
Process rating: all ten parameters 33/100
- 0Tools and files. 2 referenced file(s) missing: references/<file>.md, references/meta-levers.md
- 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
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 14 mutating operations with no state check
- 70Execution cost. Instruction body is 4216 tokens
- 100Steps. 30 steps
- 100Consistency. Name and required fields are in place
- 100Progress reporting. Reports progress
- medium Safety rules and hard prohibitions inside a skill: they belong in the system prompt, here they protect nothing
- low The response is described with custom markup (26 tags): a typed call is more reliable
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)
- +3Output format is not stated: the model decides each time
- +4No input/output examples
- +1No license
- +2Single-language instructions
- +3Description length 316: enough signal without eating the budget
- +4Structure: 6 headings
- +3Step-by-step instructions: 30 items
Quality base 70; lint remarks subtract, signals add up to 100. Result: 71.