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/seo-auditnpx skills add anthropics/knowledge-work-plugins --skill seo-auditgit 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/seo-audit)<a href="https://agentmods.dev/skills/anthropics/knowledge-work-plugins/seo-audit"><img src="https://agentmods.dev/badge/skills/anthropics/knowledge-work-plugins/seo-audit.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 | $0.00061 | $0.01970 |
| Opus 5 | $0.00030 | $0.00985 |
| Sonnet 5 | $0.00012 | $0.00394 |
| Haiku 4.5 | $0.00006 | $0.00197 |
Grade A, and why
seo-audit 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
2 near-identical copies found in the catalogue:
- seo-audit — 97% identical, 10 lines differ
- seo-audit-th — 91% identical, 12 lines differ
How it starts
The opening of the file, as written. The whole thing — 191 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/seo-audit
If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md.
Audit a website's SEO health, research keyword opportunities, identify content gaps, and benchmark against competitors. Produces a prioritized action plan a marketer can execute immediately.
Trigger
User runs /seo-audit or asks for an SEO audit, keyword research, content gap analysis, technical SEO check, or competitor SEO comparison.
Inputs
Gather the following from the user. If not provided, ask before proceeding:
-
URL or domain — the site to audit, or a topic/keyword if running in keyword research mode
-
Audit type — one of:
- Full site audit — end-to-end SEO review covering all sections below
- Keyword research — identify keyword opportunities for a topic or domain
- Content gap analysis — find topics competitors rank for that you don't
- Technical SEO check — crawlability, speed, structured data, and infrastructure issues
- Competitor SEO comparison — head-to-head SEO benchmarking against specific competitors
If not specified, default to full site audit.
-
Target keywords or topics (optional) — specific keywords the user is already targeting or wants to rank for
-
Competitors (optional) — domains or companies to compare against. If not provided and the audit type requires competitor data, use web search to identify 2-3 likely competitors based on the user's domain and keyword space.
Process
1. Keyword Research
Research keywords related to the user's domain, topic, or target keywords.
If ~~SEO tools are connected:
- Pull keyword data, search volume, keyword difficulty scores, and ranking positions automatically
- Identify keywords the site currently ranks for and where it's gaining or losing ground
If ~~product analytics are connected:
- Cross-reference keyword targets with actual organic traffic data to validate which keywords are driving visits and conversions
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 · 191 lines · 61 tokens per session scan A 25008ccdda6f
seo-audit is a skill published in the GitHub repository anthropics/knowledge-work-plugins (23,849 stars, last pushed yesterday), licensed Apache-2.0. It adds 61 tokens to every session and 1,970 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.
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…