跳到正文
cccskills
免费在 GitHub 公开

quality-assurance-auditor

Perform the final submission-level audit of mathematical-modeling workflow integrity, evidence quality, anti-fabrication, paper coherence, figures, references, and contest readiness after consistency and completeness audits pass.

中文简介正在准备中。当前显示原文说明。

实测评分 未实测

查看安装方法

包含的文件(1)

  • SKILL.md2.3 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Preconditions

  • rigor_profile is submission.
  • All Qx reached G5.
  • Final consistency and completeness audits exist.

Audit Dimensions

  1. Workflow integrity

    • G1–G5 passed per Qx.
    • Human judgments trace to the decision ledger.
    • Main/baseline/fallback execution respected approved scope.
  2. Evidence integrity

    • No fabricated data, references, experiments, metrics, or figures.
    • Main claims trace to frozen numbers and robustness evidence.
    • Limitations and uncertainty are visible.
  3. Method quality

    • Baseline is usable.
    • Assumptions, units, objectives, constraints, and solution steps are coherent.
    • Output concentration/degeneracy and failure triggers were addressed.
  4. Paper quality

    • Problem, method, results, and conclusions align.
    • Claims are proportional to tested comparisons.
    • Human-owned physical meaning and contribution are present.
  5. Presentation

    • Required figures/tables exist and passed render checks.
    • Figure types are used correctly.
    • References are real, complete, and consistently cited.
    • AI-use disclosure follows the current contest profile and verified rules.

Workflow

  1. Read the two earlier audits and unresolved blockers.
  2. Sample canonical sources directly; do not trust summaries alone.
  3. Record blocking and nonblocking findings with artifact paths and repair owners.
  4. Save paper/qa_report.md.
  5. Set verdict:
    • PASSED
    • FAILED
    • NOT_RUN

Rules

  • Do not approve on partial audits.
  • Do not use artifact count or bullet count as a proxy for quality.
  • Do not repair issues inside QA.
  • Do not hide uncertainty or downgrade a blocker silently.
  • Do not claim compliance with time-varying contest rules without verification.

Verification

  • All five audit dimensions were evaluated.
  • Blocking findings are explicit and actionable.
  • QA verdict agrees with consistency/completeness verdicts and sampled evidence.
  • Final assembly is recommended only when all three audits pass.

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Detect whether approved modeling code is Python or MATLAB/Beita Tianyuan and route it to the matching reviewer using the compact named-check review contract.

中文简介正在准备中。当前显示原文说明。

zhnnky329/MathModeling-skills10692026年9月24日 更新

Audit whether the semantic evidence required by the active lean or submission profile exists and is current, without requiring one verbose artifact per skill or an arbitrary number of pass bullets.

中文简介正在准备中。当前显示原文说明。

zhnnky329/MathModeling-skills10692026年9月24日 更新

Run scoped or final cross-media consistency checks for mathematical-modeling artifacts, comparing canonical numbers, symbols, parameters, decisions, files, and paper claims without performing full-workspace audits for low-risk changes.

中文简介正在准备中。当前显示原文说明。

zhnnky329/MathModeling-skills10692026年9月24日 更新

Map contest attachments to subquestions, audit and clean raw data, and emit one reusable data profile with quality, coverage, imbalance, concentration, and method-readiness evidence for downstream risk screening.

中文简介正在准备中。当前显示原文说明。

zhnnky329/MathModeling-skills10692026年9月24日 更新

Build one compact choice card at a genuine mathematical-modeling judgment point. Use before method screening, after a meaningful experiment, or before final claim/freeze approval so the human chooses the trade-off while AI handles mechanical consequences.

中文简介正在准备中。当前显示原文说明。

zhnnky329/MathModeling-skills10692026年9月24日 更新

Plan the smallest set of diagnostic, comparison, paper, and appendix figures or tables needed to support verified mathematical-modeling decisions and claims.

中文简介正在准备中。当前显示原文说明。

zhnnky329/MathModeling-skills10692026年9月24日 更新

查看 zhnnky329 的全部技能

报告此技能的问题