contradiction-analysis
矛盾分析法:把复杂问题拆成若干对立面,找出规定其他矛盾的主要矛盾及其主要方面,判定对抗性 /...
What this skill does for you
矛盾分析法:把复杂问题拆成若干对立面,找出规定其他矛盾的主要矛盾及其主要方面,判定对抗性 / 非对抗性,并据此选择处理方式。当问题头绪多、多个因素互相牵制、优先级不清、根因不明、反复修不好、trade-off 说不清时触发;直接执行类任务或用户已定方案时不触发。 English: Contradiction analysis. Decompose a tangled problem into opposing forces, isolate the principal contradiction and its dominant side, classify it as antagonistic or non-antagonistic, and choose the response accordingly. Trigger on unclear priorities, unknown root causes, recurring failures, or trade-offs that resist explanation; skip for direct execution or when the user has already chosen the solution.
Quoted from the skill description in the pinned sourceWho made it
Use it with Edge
Set up Edge for me: read getedge.cc/SKILL.md and follow it. Then use Edge to load the contradiction-analysis skill from hughyau/qiushi-skill.
Paste it into Claude, ChatGPT, Codex or Cursor.
Or read the skill source first.
Security evidence
| Scanner | Date | Result | Findings |
|---|---|---|---|
| Edge static checks | 2026-09-27 | Pass | 0 |
| Cisco skill-scanner | 2026-09-27 | Pass | 0 |
| Semgrep Edge rules | 2026-09-27 | Pass | 0 |
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: 3d36c1471081d0cedce248836522c6e845f9b516. 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: 3d36c1471081d0cedce248836522c6e845f9b516. 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: 3d36c1471081d0cedce248836522c6e845f9b516. Raw findings: . Counted findings: .
Source and licence
- Repository
- https://github.com/hughyau/qiushi-skill
- Pinned skill file
- View source at revision
- Revision
- 3d36c1471081d0cedce248836522c6e845f9b516
- Package hash
- sha256:598b19792f756c6f167c3d9c3e2382ee876487d5d3149dbe769dba735ac54510
- Licence
- MIT