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
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add anthropics/knowledge-work-plugins --skill weekly-prep-briefgit clone --depth 1 https://github.com/anthropics/knowledge-work-pluginsWrote 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/weekly-prep-brief)<a href="https://agentmods.dev/skills/anthropics/knowledge-work-plugins/weekly-prep-brief"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/weekly-prep-brief/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/anthropics/knowledge-work-plugins/weekly-prep-brief"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/weekly-prep-brief.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- 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 | $0.00054 | $0.01152 |
| Opus 5.5 | $0.00022 | $0.00461 |
| Sonnet 5.5 | $0.00011 | $0.00230 |
| Haiku 4.5 | $0.00005 | $0.00115 |
Grade A, and why
weekly-prep-brief 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 1mo 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
3 near-identical copies found in the catalogue:
- weekly-prep-brief — 100% identical, 0 lines differ
- weekly-prep-brief — 100% identical, 0 lines differ
- weekly-prep-brief — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Weekly Prep Brief
Generate a single comprehensive weekly briefing that covers every external customer or prospect call in the next 7 days, with per-meeting account and contact research from Common Room.
Briefing Process
Step 1: Get the Week's External Meetings
Option A — Calendar connected:
Use the ~~calendar connector to fetch all meetings scheduled in the next 7 days (or a user-specified range). Filter to keep only external meetings — those with attendees from outside your organization. Discard internal-only meetings, one-on-ones with colleagues, and recurring internal syncs.
Identify for each external meeting:
- Company name
- Meeting date and time
- External attendee names and email addresses
Option B — No calendar connected: Ask the user: "To build your weekly prep brief, I'll need your upcoming external calls. Please list them: company name, date/time, and attendee names."
Accept freeform input and parse it into a structured list before proceeding.
Step 2: Confirm the Meeting List
Present the identified meetings to the user for confirmation before beginning research:
"Here are the external calls I found for this week. Let me know if anything's missing or should be excluded:
- [Company] — [Day], [Time] — [Attendees]
- ..."
This prevents wasted research on cancelled or incorrect meetings.
Step 3: Research Each Meeting
For each confirmed external meeting, run in parallel where possible:
- Account research — full account snapshot using the account-research skill
- Contact research — profile for each external attendee using the contact-research skill
Common Room data is the primary source. After CR research, run a quick recency check for each company — this is supplementary, not primary:
- Search
"[company name]" newsscoped to the last 7 days - For executive attendees, search their name for recent public posts or interviews
- Only include findings that are genuinely noteworthy (funding, leadership changes, major press). Don't pad the brief with generic news.
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 127 lines · 54 tokens per session scan A 3c6a45f653a6
weekly-prep-brief is a skill published in the GitHub repository anthropics/knowledge-work-plugins (33,434 stars, last pushed today), licensed Apache-2.0. It adds 54 tokens to every session and 1,152 once invoked, about $0.0002 per session on Opus 5.5. 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.
Other skills, from other repositories
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…
insight-error-page
Write or audit an insight-kind error page for the Next.js dev overlay. Use when creating a new errors/ .mdx page, auditing an existing one, or checking that a page matches the framework fix cards. Covers page structure, title alignment, FixCard cards with Copy prompt button, code snippets, terminology verification…