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/people-reportWrote 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/people-report)<a href="https://agentmods.dev/skills/anthropics/knowledge-work-plugins/people-report"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/people-report.svg" alt="Measured on agentmods" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
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 | $0.00050 | $0.00631 |
| Opus 5 | $0.00025 | $0.00316 |
| Sonnet 5 | $0.00010 | $0.00126 |
| Haiku 4.5 | $0.00005 | $0.00063 |
Grade A, and why
people-report 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 4d 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:
- people-report — 92% identical, 9 lines differ
How it starts
The opening of the file, as written. The whole thing — 100 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/people-report
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Generate people analytics reports from your HR data. Analyze workforce data to surface trends, risks, and opportunities.
Usage
/people-report $ARGUMENTS
Report Types
Headcount: Current org snapshot — by team, location, level, tenure Attrition: Turnover analysis — voluntary/involuntary, by team, trends Diversity: Representation metrics — by level, team, pipeline Org Health: Span of control, management layers, team sizes, flight risk
Key Metrics
Retention
- Overall attrition rate (voluntary + involuntary)
- Regrettable attrition rate
- Average tenure
- Flight risk indicators
Diversity
- Representation by level, team, and function
- Pipeline diversity (hiring funnel by demographic)
- Promotion rates by group
- Pay equity analysis
Engagement
- Survey scores and trends
- eNPS (Employee Net Promoter Score)
- Participation rates
- Open-ended feedback themes
Productivity
- Revenue per employee
- Span of control efficiency
- Time to productivity for new hires
Approach
- Understand what question they're trying to answer
- Identify the right data (upload, paste, or pull from ~~HRIS)
- Analyze with appropriate statistical methods
- Present findings with context and caveats
- Recommend specific actions based on data
What I Need From You
Upload a CSV or describe your data. Helpful fields:
- Employee name/ID, department, team
- Title, level, location
- Start date, end date (if applicable)
- Manager, compensation (if relevant)
- Demographics (for diversity reports, if available)
Output
## People Report: [Type] — [Date]
### Executive Summary
[2-3 key takeaways]
### Key Metrics
| Metric | Value | Trend |
|--------|-------|-------|
| [Metric] | [Value] | [up/down/flat] |
### Detailed Analysis
[Charts, tables, and narrative for the specific report type]
### Recommendations
- [Data-driven recommendation]
- [Action item]
### Methodology
[How the numbers were calculated, any caveats]
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.
- 4d ago First seen · 100 lines · 50 tokens per session scan A e68d00be15a6
people-report is a skill published in the GitHub repository anthropics/knowledge-work-plugins (23,911 stars, last pushed 2d ago), licensed Apache-2.0. It adds 50 tokens to every session and 631 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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