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 agentmods add skills/anthropics/knowledge-work-plugins/discover-brandnpx skills add anthropics/knowledge-work-plugins --skill discover-brandgit 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/discover-brand)<a href="https://agentmods.dev/skills/anthropics/knowledge-work-plugins/discover-brand"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/discover-brand.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 | $0.00115 | $0.01428 |
| Opus 5 | $0.00057 | $0.00714 |
| Sonnet 5 | $0.00023 | $0.00286 |
| Haiku 4.5 | $0.00012 | $0.00143 |
Grade A, and why
discover-brand 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 yesterday.
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:
- discover-brand — 100% identical, 0 lines differ
- discover-brand — 100% identical, 0 lines differ
- discover-brand — 98% identical, 14 lines differ
How it starts
The opening of the file, as written. The whole thing — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Brand Discovery
Orchestrate autonomous discovery of brand materials across enterprise platforms. This skill coordinates the discover-brand agent to search connected platforms (Notion, Confluence, Google Drive, Box, Microsoft 365, Figma, Gong, Granola, Slack), triage sources, and produce a structured discovery report with open questions.
Discovery Workflow
0. Orient the User
Before starting, briefly explain what's about to happen so the user knows what to expect:
"Here's how brand discovery works:
- Search — I'll search your connected platforms (Notion, Google Drive, Slack, etc.) for brand-related materials: style guides, pitch decks, templates, transcripts, and more.
- Analyze — I'll categorize and rank what I find, pull the best sources, and produce a discovery report with what I found, any conflicts, and open questions.
- Generate guidelines — Once you've reviewed the report, I can generate a structured brand voice guideline document from the results.
- Save — Guidelines are saved to
.claude/brand-voice-guidelines.mdin your working folder once you approve them. Nothing is written until that step.
The search usually takes a few minutes depending on how many platforms are connected. Ready to get started?"
Wait for the user to confirm before proceeding. If they have questions about the process, answer them first.
1. Check Settings
Read .claude/brand-voice.local.md if it exists. Extract:
- Company name
- Which platforms are enabled (notion, confluence, google-drive, box, microsoft-365, figma, gong, granola, slack)
- Search depth preference (standard or deep)
- Max sources limit
- Any known brand material locations listed under "Known Brand Materials"
If no settings file exists, proceed with all connected platforms and standard search depth.
2. Validate Platform Coverage
Before confirming scope, check which platforms are actually connected and classify them:
Document platforms (where brand guidelines, style guides, templates, and decks live):
- Notion, Confluence, Google Drive, Box, Microsoft 365 (SharePoint/OneDrive)
What ships with it
2 files 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.
- yesterday First seen · 128 lines · 115 tokens per session scan A 4d5d4490a160
discover-brand is a skill published in the GitHub repository anthropics/knowledge-work-plugins (23,849 stars, last pushed yesterday), licensed Apache-2.0. It adds 115 tokens to every session and 1,428 once invoked, about $0.0006 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
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…