Knowledge Work Plugins is an open-source collection of Claude extensions organized around roles such as productivity, sales, and customer support. Each plugin combines role-specific guidance, connectors, commands, and sub-agents so knowledge workers can use Claude with their team’s tools and processes. The catalogue entries are examples of, or workflows from, this plugin collection.
Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/anthropics/knowledge-work-pluginsnpx agentmods add skills/anthropics/knowledge-work-plugins/performance-reviewWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/anthropics/knowledge-work-plugins/performance-review)<a href="https://agentmods.dev/skills/anthropics/knowledge-work-plugins/performance-review"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/performance-review.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00061 | $0.01113 |
| Opus 5 | $0.00030 | $0.00557 |
| Sonnet 5 | $0.00012 | $0.00223 |
| Haiku 4.5 | $0.00006 | $0.00111 |
Grade A, and why
performance-review scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 3d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
1 near-identical copy found in the catalogue:
- performance-review — 89% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 150 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/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]
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 3d ago First seen · 150 lines · 61 tokens per session scan A a34e3f49e7c8
performance-review is a skill published in the GitHub repository anthropics/knowledge-work-plugins (23,902 stars, last pushed yesterday), licensed Apache-2.0. It adds 61 tokens to every session and 1,113 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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