Skill profile

confidence-check

Pre-implementation confidence assessment (≥90% required).

What this skill does for you

Pre-implementation confidence assessment (≥90% required). Use before starting any implementation to verify readiness with duplicate check, architecture compliance, official docs verification, OSS references, and root cause identification.

Quoted from the skill description in the pinned source

Who made it

Publishersuperclaude-org

Repositorysuperclaude_framework

Installs310as of Sep 27, 2026

Use it with Edge

Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the confidence-check skill from superclaude-org/superclaude_framework.

Paste it into Claude, ChatGPT, Codex or Cursor.

Or read the skill source first.

Security evidence

Security state at 2026-09-30: reviewed. State definitions. This records static evidence for this revision; live load eligibility is checked again.

3 static scans, 0 counted findings. The listed scanners recorded the results shown for this package revision.

Scanner	Date	Result
Edge static checks	2026-09-27	Pass
Cisco skill-scanner	2026-09-27	Pass
Semgrep Edge rules	2026-09-27	Pass

Static scans check the code, not how well the skill works.

Scanner scope, raw findings and mirrored provider records

Edge static checks (Edge-run): edge-static/1.0.1. Scope: Static patterns for remote execution, credentials with network sends, obfuscation, prompt overrides, hidden Unicode, binaries and persistence. Revision: 2d0fda08f2eed9951794dc9c54a6289454961075. Raw findings: . Counted findings: .

Cisco skill-scanner (Edge-run): cisco-skill-scanner/2.1.0. Scope: Local static, YARA, pipeline and behavioral analyzers; no LLM or AI Defense analysis. Revision: 2d0fda08f2eed9951794dc9c54a6289454961075. Raw findings: 2. Counted findings: .

Semgrep Edge rules (Edge-run): semgrep/1.178.0+edge-rules.c15016a36fd3+offline-v1. Scope: Six Edge-authored static rules with Semgrep CE; offline execution and metrics disabled. Semgrep-maintained rules excluded. Revision: 2d0fda08f2eed9951794dc9c54a6289454961075. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/superclaude-org/superclaude_framework
Pinned skill file: View source at revision
Revision: 2d0fda08f2eed9951794dc9c54a6289454961075
Package hash: sha256:28cd1b8f8da933e70fa22be4af048c1b5650bc6f1c76ae730f468c07d773c432
Licence: MIT