Skill profile

self-review

Use when doing dev-stage self-review on the current branch before pushing or opening a PR : runs an...

What this skill does for you

Use when doing dev-stage self-review on the current branch before pushing or opening a PR : runs an auto-loop of codex review (cross-model, OpenAI) + per-finding fix + re-review until findings converge or stop conditions fire. Codex follows pr-review's multi-role methodology (security / staff-engineer / sdet / spec-auditor). Triggers : 'self review', 'self-review', '自己 review', '自我 review', 'cross-model review', 'pre-push review', 'review and fix my branch'. NOT for live PR review with sticky/inline comments (use pr-review), NOT for managed PR babysitting (use pr-babysit), NOT for first-time review without intent to fix (use mode=review-only opt-in).

Quoted from the skill description in the pinned source

Who made it

Publisherkirkchen

Repositorycadence

Installs380as 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 self-review skill from kirkchen/cadence.

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: a0b6e2eac42e09ce22eb035c7b0d12421ca6a40b. 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: a0b6e2eac42e09ce22eb035c7b0d12421ca6a40b. Raw findings: 1. 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: a0b6e2eac42e09ce22eb035c7b0d12421ca6a40b. Raw findings: . Counted findings: .

Source and licence

Repository: https://github.com/kirkchen/cadence
Pinned skill file: View source at revision
Revision: a0b6e2eac42e09ce22eb035c7b0d12421ca6a40b
Package hash: sha256:ceb9fd2290920c981fbe105efa6f4a4cae688375426c3b565b610ad2d3d6dca9
Licence: MIT