跳到正文
cccskills
免费在 GitHub 公开

codexkit-talent-review-calibrator

Facilitate talent review and people decisions with a structured view of performance, potential, readiness, risks, and development actions using talent calibration and 9-box logic. Use when preparing talent review, succession planning, promotion readiness, or performance calibration sessions. Do not use for payroll administration, HRIS updates, or generic praise notes.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(2)

  • SKILL.md3.2 KB
  • agents/openai.yaml202 B

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Talent Review Calibrator

Purpose

Support fairer and more actionable talent discussions by structuring evidence, risk, and development actions.

When to use

  • Leaders are preparing a talent review or succession discussion.
  • Managers need calibration before promotion or performance decisions.
  • HR wants consistent talent cards and action plans.

When not to use

  • The task is a transactional HR operation.
  • There is no evidence beyond vague opinion or hearsay.

Inputs

  • employee or talent pool list
  • recent performance evidence and outcomes
  • potential indicators, readiness signals, and role criticality
  • retention risk, succession context, or capability gaps

Procedure

  1. Define the evaluation lens and remove criteria drift before rating people.
  2. Separate evidence, interpretation, and bias risks.
  3. Place talent using performance, potential, and readiness signals.
  4. Identify critical-role coverage, succession gaps, and flight risk.
  5. Recommend development, retention, promotion, or watch actions.
  6. Flag where calibration evidence is weak or inconsistent.

Output

  • talent calibration summary
  • per-person talent cards
  • 9-box or equivalent placement rationale
  • succession and retention risk view
  • action plan with owners and timing

Definition of done

  • Each recommendation ties back to evidence.
  • Critical talent risks and succession gaps are visible.
  • The output is usable in an actual calibration session.

Examples

  • "Prepare a talent review pack for our engineering and operations managers."
  • "Calibrate promotion readiness for these six employees and identify development actions."

Quality Criteria

  • Feedback is specific and references exact locations in the reviewed material
  • Each critique includes a concrete improvement suggestion
  • Severity is categorized (critical / important / nice-to-have)
  • Positive aspects are acknowledged alongside areas for improvement

Verification (4C)

CheckQuestion
CorrectnessIs the feedback technically accurate and properly contextualized?
CompletenessWere all major sections of the reviewed material addressed?
Context-fitIs the review granularity appropriate for the material's maturity level?
ConsequenceIf the author implemented all feedback literally, what could go wrong?

Edge Cases

  • Material is too early-stage for detailed review — Provide structural feedback only. Note that content review is deferred until it matures.
  • Reviewer lacks domain expertise — Focus on structure, clarity, and consistency. Flag domain-specific claims as 'Needs SME verification'.
  • Author is defensive or resistant to feedback — Lead with what works well. Frame changes as questions rather than mandates.

Changelog

  • v1.0.0 — Initial release

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

Design rigorous A/B test plans with hypothesis, sample size calculation, Minimum Detectable Effect (MDE), randomization strategy, and decision rules. Includes guardrail metrics and rollout playbook. Use when planning product experiments, conversion optimization, or data-driven feature decisions.

中文简介正在准备中。当前显示原文说明。

hoavdc/CodexKit252026年10月11日 更新

Review REST and GraphQL API designs for consistency, usability, and best practices. Covers naming conventions, versioning strategy, error format, pagination, authentication patterns, and breaking change detection. Use when reviewing API specs, designing new APIs, or auditing existing endpoints.

中文简介正在准备中。当前显示原文说明。

hoavdc/CodexKit252026年10月11日 更新

Write Architecture Decision Records (ADRs) following the Michael Nygard format. Captures context, options considered, decision rationale, and consequences. Use when making technology choices, framework selections, or any architectural decision that future developers need to understand.

中文简介正在准备中。当前显示原文说明。

hoavdc/CodexKit252026年10月11日 更新

Assess organizational readiness for financial audits (internal or external). Map assertions to account balances, check evidence completeness, score readiness using a Red/Amber/Green framework, and generate a remediation timeline. Aligned with SOX, IFRS, and GAAP audit standards. Use before scheduled audits or when preparing for first-time compliance.

中文简介正在准备中。当前显示原文说明。

hoavdc/CodexKit252026年10月11日 更新

Design safe recurring Codex automations with clear prompts, outputs, schedules, and gating rules.

中文简介正在准备中。当前显示原文说明。

hoavdc/CodexKit252026年10月11日 更新

Refine Product Backlog Items to meet INVEST criteria. Write User Stories with Acceptance Criteria in Given/When/Then format, estimate with Story Points, and flag dependencies. Use before sprint planning when backlog items need grooming. Do not use to prioritize the backlog — that is the Product Owner's decision.

中文简介正在准备中。当前显示原文说明。

hoavdc/CodexKit252026年10月11日 更新

查看 hoavdc 的全部技能

报告此技能的问题