FrancoStino/grill-with-docs
bundled-skills/grill-with-docs/SKILL.md
A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
$ install --global
skillsauthnpx skillsauth add FrancoStino/opencode-skills-antigravity grill-with-docsInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Jun 20, 2026, 2:54 AM36.2s1 file scanned
SKILL.md
- name:
- grill-with-docs
- description:
- A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
- disable-model-invocation:
- true
- category:
- productivity
- risk:
- safe
- source:
- community
- source_repo:
- mattpocock/skills
- source_type:
- community
- date_added:
- 2026-06-19
- author:
- Matt Pocock
- license:
- MIT
- license_source:
- https://github.com/mattpocock/skills/blob/main/LICENSE
When to Use
Use when this workflow matches the user request: A relentless interview to sharpen a plan or design, which also creates docs (ADR's and glossary) as we go.
_Source: mattpocock/skills (MIT)._Run a /grilling session, using the /domain-modeling skill.
Limitations
- Requires the upstream tool, account, API key, or local setup when the workflow names one.
- Does not authorize destructive, production, paid, or external-message actions without explicit user approval.
- Validate generated artifacts or recommendations against the user's real sources before treating them as final.
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