email-sequence
No security findings. Scanned 1 time, most recently 2026-02-06.
Second scanner: NVIDIA SkillSpector
SkillSpector found no issues but could not fully inspect the package, usually because SKILL.md refers to a file that is not present, so it fails closed to CAUTION instead of SAFE. Read it as "not fully checked", not as a finding. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
When the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.
- Package
- 4 files, 27 KB
- SKILL.md
- 1099 words, 12+ sections
- Code
- None. Instructions only.
- Version
- 1.0.0
SKILL.md covers: Email Sequence Design · Initial Assessment · Core Principles · 1. One Email, One Job · 2. Value Before Ask · 3. Relevance Over Volume · 4. Clear Path Forward · Email Sequence Strategy · Sequence Length · Timing/Delays · Subject Line Strategy · Preview Text
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 7.7 KB |
references/copy-guidelines.md | doc | 2.0 KB |
references/email-types.md | doc | 13 KB |
references/sequence-templates.md | doc | 3.7 KB |
Package contents recorded 2026-10-22 at commit a04cb61a577a. The scan above ran against the version current at scan time; the two can differ if the skill has since been updated.
What we checked
- Static analyzer. Pattern rules over SKILL.md and bundled files: known-bad commands, exfiltration URLs, secrets, obfuscation.
- Behavioral analyzer. Checks what the skill asks the agent to do against what its description claims it does.
- Llm analyzer. A language model reads the skill and reports intent-level issues the rules cannot express.
- Trigger analyzer. Looks for instructions that fire on conditions the user did not ask for.
- Meta analyzer. A second model pass that validates, deduplicates and re-scores the other analyzers' findings.
What we did not check
- Runtime behaviour. The skill was not executed; findings come from reading its files.
- Anything fetched at install or run time, including remote scripts, package dependencies, and URLs the skill tells the agent to open.
- Content the analyzers cannot read: images, binaries, and some non-English text.
- Known scanner bypass classes. See the methodology and limitations page.
Sources
- Repository: https://github.com/coreyhaines31/marketingskills
- Raw scan result: email-sequence-scan.json
- Badge for your README:
- Request a re-scan