Claude Cowork AI Skills
Anthropic's desktop agent for multi-step workflows
Claude Cowork is Anthropic's desktop application that brings agentic capabilities to your computer. Skills integrate via MCP to add specialized tools for document analysis, workflow automation, and complex multi-step tasks - all accessible through a rich graphical interface.
Top Claude Cowork Skills
Cognitive Anchor Sketcher for Chinese Articles
Turn Chinese articles into hand-drawn visuals that explain the idea instead of simply decorating the page. Cognitive Anchor Sketcher reads the article, finds the strongest judgments, turning points, structures, states, and metaphors, then builds a focused shot list before image generation. Each illustration communicates one idea in a clean 16:9 composition with a white background, black hand-drawn linework, generous whitespace, and short Chinese annotations. Use it for newsletters, blogs, Notion pages, product thinking, workflow documents, and methodology content. Choose between minimal-line and emotion-doodle styles, use the included Xiaohei, Tuotuo, and Xingbi characters, or work with an authorized custom IP. A guided QA flow confirms the direction, style, IP, shot list, and output settings. It can also provide cognitive-anchor analysis and illustration planning without generating images. Image generation requires a ChatGPT-authenticated Codex CLI session.
Popular Platform Data Collection Skill
Popular Platform Data Collection Skill is an agent workflow for authorized content research, content archiving, and first-party account backups. It guides users to manually export public, owned, or clearly authorized videos, cover images, page copy, tags, engagement data, and comments through DATATOOL. It validates the input files, uses local OpenAI Whisper to transcribe the complete video audio track, anonymizes comment data when requested, and produces a verifiable Chinese ZIP package containing Excel files, text, subtitles, segmented JSON, and a SHA-256 manifest. Users handle DATATOOL installation, login, verification, authorization, and content export in a normal browser. The Skill does not control DATATOOL, store cookies or passwords, bypass captchas, paywalls, private-content restrictions, or anti-bot controls. Videos are transcribed locally by default and are not uploaded to third-party transcription services.
Project Sentinel - Multi-Project Development Progress Tracker
ENHE Project Sentinel is a local-first, read-only Skill for tracking multiple development projects. It reads authorized Git repositories, project documents, reports, quality signals, and available Codex usage data to generate bilingual project portfolio reports. Reports include progress, elapsed development time, ETA ranges, risks, quality signals, Codex context, token usage, next actions, and agent-ready prompts. It is designed for indie developers, AI product builders, product owners, and small R&D teams. Supports Windows 10/11. By default, it does not modify project code or upload source code, and it clearly marks insufficient evidence instead of inventing precise ETAs.
Verify Paid Work Before Starting
Paid-looking work can fail before implementation: the payer may be unverified, the issue may already be saturated, the rules may prohibit the submission, the requested result may be impossible to validate, or payment may depend on an undefined review. This gate instructs the agent to prove the commercial path before it commits time, credentials, reputation, or money. It checks buyer authority, amount and payment rail, assistance and eligibility rules, full deliverability, repository safety, competition, acceptance evidence, and time-to-cash. Four competitive levers produce a 0-100 score, but hard safety and payability gates always win. The result is one clear PROCEED or BLOCK decision with mandatory scope, exact blockers, a proof plan, the next bounded action, a stop condition, and the official evidence that would justify reconsideration.
What Claude Cowork skills can do for you
Desktop-Native Agent
Claude Cowork operates as a full desktop agent, controlling your computer to complete complex tasks. Skills give it specialized capabilities for your specific workflows.
Multi-Step Workflows
Cowork handles multi-step tasks autonomously - research, draft, edit, publish. Skills extend these workflows with domain-specific actions and integrations.
Seamless MCP Integration
Skills register as MCP servers that Claude Cowork discovers automatically. Configure once in your settings and every skill is ready to use.
Claude Cowork Skills
Cognitive Anchor Sketcher for Chinese Articles
Turn Chinese articles into hand-drawn visuals that explain the idea instead of simply decorating the page. Cognitive Anchor Sketcher reads the article, finds the strongest judgments, turning points, structures, states, and metaphors, then builds a focused shot list before image generation. Each illustration communicates one idea in a clean 16:9 composition with a white background, black hand-drawn linework, generous whitespace, and short Chinese annotations. Use it for newsletters, blogs, Notion pages, product thinking, workflow documents, and methodology content. Choose between minimal-line and emotion-doodle styles, use the included Xiaohei, Tuotuo, and Xingbi characters, or work with an authorized custom IP. A guided QA flow confirms the direction, style, IP, shot list, and output settings. It can also provide cognitive-anchor analysis and illustration planning without generating images. Image generation requires a ChatGPT-authenticated Codex CLI session.
Popular Platform Data Collection Skill
Popular Platform Data Collection Skill is an agent workflow for authorized content research, content archiving, and first-party account backups. It guides users to manually export public, owned, or clearly authorized videos, cover images, page copy, tags, engagement data, and comments through DATATOOL. It validates the input files, uses local OpenAI Whisper to transcribe the complete video audio track, anonymizes comment data when requested, and produces a verifiable Chinese ZIP package containing Excel files, text, subtitles, segmented JSON, and a SHA-256 manifest. Users handle DATATOOL installation, login, verification, authorization, and content export in a normal browser. The Skill does not control DATATOOL, store cookies or passwords, bypass captchas, paywalls, private-content restrictions, or anti-bot controls. Videos are transcribed locally by default and are not uploaded to third-party transcription services.
Project Sentinel - Multi-Project Development Progress Tracker
ENHE Project Sentinel is a local-first, read-only Skill for tracking multiple development projects. It reads authorized Git repositories, project documents, reports, quality signals, and available Codex usage data to generate bilingual project portfolio reports. Reports include progress, elapsed development time, ETA ranges, risks, quality signals, Codex context, token usage, next actions, and agent-ready prompts. It is designed for indie developers, AI product builders, product owners, and small R&D teams. Supports Windows 10/11. By default, it does not modify project code or upload source code, and it clearly marks insufficient evidence instead of inventing precise ETAs.
Verify Paid Work Before Starting
Paid-looking work can fail before implementation: the payer may be unverified, the issue may already be saturated, the rules may prohibit the submission, the requested result may be impossible to validate, or payment may depend on an undefined review. This gate instructs the agent to prove the commercial path before it commits time, credentials, reputation, or money. It checks buyer authority, amount and payment rail, assistance and eligibility rules, full deliverability, repository safety, competition, acceptance evidence, and time-to-cash. Four competitive levers produce a 0-100 score, but hard safety and payability gates always win. The result is one clear PROCEED or BLOCK decision with mandatory scope, exact blockers, a proof plan, the next bounded action, a stop condition, and the official evidence that would justify reconsideration.
Hikvision NVR
Ask your AI agent for the Hikvision footage you need, then walk away while it downloads. Pulling video off a Hikvision DVR or NVR usually means web-UI menus, ISAPI XML, ffmpeg flags, and "why is this video broken" troubleshooting. This skill removes all of it. Once your NVRs are registered, you just tell your agent "pull the lobby camera from 8 to 9 PM yesterday" and a clean MP4 lands in your downloads folder. Speaks Hikvision's ISAPI natively, falls back to RTSP when the NVR throttles, works around firmware quirks that return wrong segment data, clips to the exact time window you asked for, and verifies the output (codec, resolution, duration, on-screen timestamp). Credentials live in your OS keychain, never on command lines or in logs. Validated on DS-9016HWI-ST, DS-7316HQHI-SH, DS-7716NI-I4/16P, DS-9632NI-ST, and DS-7716NI-SP/16 with firmware V3.1.10 through V4.50.000.
AgentPass Local
Install a local credential broker with a desktop GUI, allowed-domain policy checks, and OS-protected sensitive fields. Use it when an approved agent workflow needs a narrow login or API handoff without putting passwords, tokens, recovery codes, or payout details into chat, logs, screenshots, or repositories.
mesh flow
What it does Mesh Flow replaces fragile, implicit prompt-chaining with a robust, artifact-driven DAG (Directed Acyclic Graph) orchestration system. By defining your agent workflows in a structured project.yaml, you move logic out of the prompt and into a compile-time validated system. It enforces hard gates—such as human approval or dependency verification—that the AI cannot bypass or hallucinate past. Why use this skill Standard agentic workflows often fail because the LLM decides to skip steps or "forgets" requirements. Mesh Flow treats your agentic workflow like a CI/CD pipeline. It features a Compile-then-Run architecture that validates your topology for cycles and missing artifacts before single token is generated. This ensures 100% predictable execution paths, explicit failure states (failed, blocked, rejected), and absolute control over recovery paths. Supported tools YAML-based workflow configurations Standardized Adapter Interfaces for cross-skill communication Mermaid DAG visualization for debugging Zod-backed schema validation CLI tools for compilation and execution (mesh compile, mesh run) Output structure The skill produces a normalized execution plan and a detailed execution trace. Every node execution returns a standardized status, a list of produced artifacts, and comprehensive metadata including tool calls and verification reasoning. Use Cases Build multi-step agent pipelines with hard verification gates Enforce human-in-the-loop approval before sensitive code deployments Visualize complex agent task dependencies using Mermaid DAGs Standardize artifact sharing between disparate AI skills and agents
De-Woke AI Responses
Looking for a sharp, rule-bending prompt? This powerful analysis flips the script on "dominant paradigms," demanding honest, bias-busting answers from AI. It spotlights cultural power shifts, challenges system dogma, and forces truly independent thinking in any model you use. Make your AI face the hard questions—get real answers, not programmed ones. De-woke your writing!
Common questions about Claude Cowork skills
How do skills work with Claude Cowork?
Skills are installed as MCP servers that Claude Cowork connects to. Once configured, you can ask Claude to use any installed skill during your workflows.
Can I use the same skills in Claude Code and Claude Cowork?
Yes. Most skills work across both Claude Code and Claude Cowork since they both support the MCP protocol. Your license covers all compatible platforms.
Do I need developer experience to use skills in Claude Cowork?
Not at all. Claude Cowork is designed for everyone. Skills install with a simple configuration change and are then available through natural conversation.
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