AD sequenzy-email-marketing
Primary agent guide for operating Sequenzy as an email-marketing platform. Use when Codex needs to authenticate, inspect identity, manage subscribers, create or edit campaigns/sequences/templates, control the campaign lifecycle (cancel, pause, resume, delete, duplicate), run campaign A/B tests, mutate lists/tags/segments, enroll subscribers into sequences, invite team members, triage and reply to inbox conversations, manage outbound webhooks, generate draft email content, send transactional email, read delivery stats, or decide whether a requested Sequenzy email-marketing workflow is currently supported. Prefer this over the generic sequenzy skill when both seem relevant.
As a process D 48/100 · Unfinished process — weak spots: result and completion, when it triggers, inputs and preconditions
How to improve
- 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: 5. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 48/100
- 0Result and completion. Does not say what the result is
- 0Inputs and preconditions. Does not say what the process needs to start
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 30Running it twice. 66 mutating operations with no state check
- 60Tools and files. Uses tools (node) that frontmatter does not declare
- 65Failures and branches. 3 branches
- 85Steps. 63 steps, 1 vague phrases
- 100Consistency. Name and required fields are in place
- 100Execution cost. Instruction body is 3233 tokens
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 680: enough signal without eating the budget
- +4Structure: 8 headings
- +3Step-by-step instructions: 63 items
- +4Reference files are cited in the instructions (2 of 2)
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.