social-content
No security findings. Scanned 1 time, most recently 2026-02-01.
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 help creating, scheduling, or optimizing social media content for LinkedIn, Twitter/X, Instagram, TikTok, Facebook, or other platforms. Also use when the user mentions 'LinkedIn post,' 'Twitter thread,' 'social media,' 'content calendar,' 'social scheduling,' 'engagement,' or 'viral content.' This skill covers content creation, repurposing, and platform-specific strategies.
- Package
- 4 files, 21 KB
- SKILL.md
- 1223 words, 12+ sections
- Code
- None. Instructions only.
- Version
- 1.0.0
SKILL.md covers: Social Content · Before Creating Content · 1. Goals · 2. Audience · 3. Brand Voice · 4. Resources · Platform Quick Reference · Content Pillars Framework · Example for a SaaS Founder · Pillar Development Questions · Hook Formulas · Curiosity Hooks
Findings
No findings. SAFE
What is in the package
| File | Kind | Size |
|---|---|---|
SKILL.md | doc | 8.2 KB |
references/platforms.md | doc | 4.2 KB |
references/post-templates.md | doc | 3.3 KB |
references/reverse-engineering.md | doc | 5.3 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: social-content-scan.json
- Badge for your README:
- Request a re-scan