performance-review

anthropics/knowledge-work-plugins · updated Apr 8, 2026

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$npx skills add https://github.com/anthropics/knowledge-work-plugins --skill performance-review
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summary

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

skill.md

/performance-review

If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.

Generate performance review templates and help structure feedback.

Usage

/performance-review $ARGUMENTS

Modes

/performance-review self-assessment       # Generate self-assessment template
/performance-review manager [employee]    # Manager review template for a specific person
/performance-review calibration           # Calibration prep document

If no mode is specified, ask what type of review they need.

Output — Self-Assessment Template

## Self-Assessment: [Review Period]

### Key Accomplishments
[List your top 3-5 accomplishments this period. For each, describe the situation, your contribution, and the impact.]

1. **[Accomplishment]**
   - Situation: [Context]
   - Contribution: [What you did]
   - Impact: [Measurable result]

### Goals Review
| Goal | Status | Evidence |
|------|--------|----------|
| [Goal from last period] | Met / Exceeded / Missed | [How you know] |

### Growth Areas
[Where did you grow? New skills, expanded scope, leadership moments.]

### Challenges
[What was hard? What would you do differently?]

### Goals for Next Period
1. [Goal — specific and measurable]
2. [Goal]
3. [Goal]

### Feedback for Manager
[How can your manager better support you?]

Output — Manager Review

## Performance Review: [Employee Name]
**Period:** [Date range] | **Manager:** [Your name]

### Overall Rating: [Exceeds / Meets / Below Expectations]

### Performance Summary
[2-3 sentence overall assessment]

### Key Strengths
- [Strength with specific example]
- [Strength with specific example]

### Areas for Development
- [Area with specific, actionable guidance]
- [Area with specific, actionable guidance]

### Goal Achievement
| Goal | Rating | Comments |
|------|--------|----------|
| [Goal] | [Rating] | [Specific observations] |

### Impact and Contributions
[Describe their biggest contributions and impact on the team/org]

### Development Plan
| Skill | Current | Target | Actions |
|-------|---------|--------|---------|
| [Skill] | [Level] | [Level] | [How to get there] |

### Compensation Recommendation
[Promotion / Equity refresh / Adjustment / No change — with justification]

Output — Calibration

## Calibration Prep: [Review Cycle]
**Manager:** [Your name] | **Team:** [Team] | **Period:** [Date range]

### Team Overview
| Employee | Role | Level | Tenure | Proposed Rating | Notes |
|----------|------|-------|--------|-----------------|-------|
| [Name] | [Role] | [Level] | [X years] | [Rating] | [Key context] |

### Rating Distribution
| Rating | Count | % of Team | Company Target |
|--------|-------|-----------|----------------|
| Exceeds Expectations | [X] | [X]% | ~15-20% |
| Meets Expectations | [X] | [X]% | ~60-70% |
| Below Expectations | [X] | [X]% | ~10-15% |

### Calibration Discussion Points
1. **[Employee]** — [Why this rating may need discussion, e.g., borderline, first review at level, recent role change]
2. **[Employee]** — [Discussion point]

### Promotion Candidates
| Employee | Current Level | Proposed Level | Justification |
|----------|-------------|----------------|---------------|
| [Name] | [Current] | [Proposed] | [Evidence of next-level performance] |

### Compensation Actions
| Employee | Action | Justification |
|----------|--------|---------------|
| [Name] | [Promotion / Equity refresh / Market adjustment / Retention] | [Why] |

### Manager Notes
[Context the calibration group should know — team changes, org shifts, project impacts]

If Connectors Available

If ~~HRIS is connected:

  • Pull prior review history and goal tracking data
  • Pre-populate employee details and current role information

If ~~project tracker is connected:

  • Pull completed work and contributions for the review period
  • Reference specific tickets and project milestones as evidence

Tips

  1. Be specific — "Great job" isn't feedback. "You reduced deploy time 40% by implementing the new CI pipeline" is.
  2. Balance positive and constructive — Both are essential. Neither should be a surprise.
  3. Focus on behaviors, not personality — "Your documentation has been incomplete" vs. "You're careless."
  4. Make development actionable — "Improve communication" is vague. "Present at the next team all-hands" is actionable.
how to use performance-review

How to use performance-review on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add performance-review
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/anthropics/knowledge-work-plugins --skill performance-review

The skills CLI fetches performance-review from GitHub repository anthropics/knowledge-work-plugins and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/performance-review

Reload or restart Cursor to activate performance-review. Access the skill through slash commands (e.g., /performance-review) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.551 reviews
  • Arjun Bansal· Dec 28, 2024

    Registry listing for performance-review matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Shikha Mishra· Dec 16, 2024

    Keeps context tight: performance-review is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Arjun Abebe· Dec 12, 2024

    performance-review fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Henry Verma· Nov 19, 2024

    Useful defaults in performance-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Nikhil Mensah· Nov 3, 2024

    performance-review has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Anika Iyer· Oct 22, 2024

    Solid pick for teams standardizing on skills: performance-review is focused, and the summary matches what you get after install.

  • Charlotte Martin· Oct 10, 2024

    I recommend performance-review for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Rahul Santra· Sep 13, 2024

    performance-review has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Nia Choi· Sep 13, 2024

    Useful defaults in performance-review — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Amelia Haddad· Sep 9, 2024

    performance-review has been reliable in day-to-day use. Documentation quality is above average for community skills.

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