email-best-practices
No security findings. Scanned 1 time, most recently 2026-02-06.
Second scanner: NVIDIA SkillSpector
Independent static run, no language model, over the same files as the Cisco scan above. How the two scanners compare across the whole corpus: Two scanners, one corpus.
What this skill does
Use when building email features, emails going to spam, high bounce rates, setting up SPF/DKIM/DMARC authentication, implementing email capture, ensuring compliance (CAN-SPAM, GDPR, CASL), handling webhooks, retry logic, or deciding transactional vs marketing.
- Package
- 13 files, 51 KB
- SKILL.md
- 254 words, 4 sections
- Code
- None. Instructions only.
SKILL.md covers: Email Best Practices · Architecture Overview · Quick Reference · Start Here
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
README.md | doc | 2.5 KB |
SKILL.md | doc | 3.2 KB |
resources/branding.md | doc | 119 B |
resources/compliance.md | doc | 3.6 KB |
resources/deliverability.md | doc | 3.0 KB |
resources/email-capture.md | doc | 3.3 KB |
resources/email-types.md | doc | 5.7 KB |
resources/list-management.md | doc | 4.5 KB |
resources/marketing-emails.md | doc | 3.2 KB |
resources/sending-reliability.md | doc | 4.7 KB |
resources/transactional-email-catalog.md | doc | 10 KB |
resources/transactional-emails.md | doc | 2.4 KB |
resources/webhooks-events.md | doc | 4.2 KB |
External hosts referenced
resend.com github.com postmaster.google.com
Hostnames that appear in the skill's files. Referencing a host is not a finding; compare against the findings above and the skill's stated purpose.
Environment variables referenced
RESEND_WEBHOOK_SECRET
Package contents recorded 2026-10-22. 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://clawhub.ai/skills/email-best-practices
- Raw scan result: email-best-practices-scan.json
- Badge for your README:
- Request a re-scan