Claude Code AI Skills
AI skills built for Anthropic's terminal-native coding assistant
Claude Code runs directly in your terminal with full project context. Skills integrate as MCP tools, giving Claude deep understanding of your codebase for code generation, refactoring, testing, and documentation - all through natural conversation.
Top Claude Code Skills
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.
What Claude Code skills can do for you
Terminal-Native Workflow
Skills run directly in your terminal alongside your existing tools. No context switching - ask Claude to use a skill and it executes inline with your project.
Deep Codebase Understanding
Claude Code reads your entire project structure, so skills operate with full context. Generate tests that match your patterns, docs that reflect your architecture.
MCP Tool Integration
Skills integrate as Model Context Protocol tools, extending Claude's capabilities natively. Install once and they're available in every session.
Claude Code Skills
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!
harness-engineering
The Harness Engineering skill implements a structured methodology for agent orchestration. It allows you to build sophisticated control loops using a multi-role architecture: Planner: Defines contracts and stop rules. Executor: Performs bounded actions. Verifier: Validates results against evidence. Critic/Recovery: Identifies regressions and manages error state.
Common questions about Claude Code skills
How do I install skills in Claude Code?
Run npx @agentpowers/cli setup to auto-configure MCP for all your AI tools, then ask Claude to install any skill. Or install directly with npx @agentpowers/cli install skill-name --code YOUR-LICENSE-CODE. Legacy CLI (pip install agentpowers) also works. Skills are available immediately in your next session.
Are Claude Code skills compatible with other platforms?
Most skills on AgentPowers work across multiple MCP-compatible platforms. Check the platform badges on each skill listing to see full compatibility.
Do Claude Code skills require a paid Claude plan?
Claude Code requires a Claude API subscription. Skills from AgentPowers are purchased separately and work with any active Claude Code installation.
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