Top Claude Code Skills

Executive Summary

This article is based on the Zhihu column article Ten Top Claude Code Skills and official technical documentation. It deeply analyzes and expands the meaning and practical examples of these key skills. Claude Code uses a “Skill” mechanism, equivalent to skill plugins, to write development-process methodology into instructions so that large language models can work according to them (Anthropic Engineering, Claude Platform Docs). This article organizes ten core skills: brainstorming, writing plans, executing plans, test-driven development, systematic debugging, requesting code review, dispatching parallel agents, verification before completion, using Git worktrees, and Excalidraw diagrams. We verified the concrete practices of each skill in official documentation or community implementations, such as the obra/superpowers application framework and the Chinese enhanced version, and provide Python/JavaScript invocation examples and GitHub repository links. The article compares implementation methods and limitations across different sources, proposes learning priorities and practical exercises for the skills, and discusses common risks such as mistriggering, performance overhead, and data security, along with mitigation strategies.

Overview of the Claude Code Skill Mechanism

Anthropic formally introduced the “Agent Skills” architecture, which packages workflows and specialized knowledge into directory structures, allowing Claude to automatically load matching skills according to the task (Anthropic Engineering). A Skill must contain a SKILL.md file. The frontmatter metadata, including name and description, is first loaded into the system prompt, and when the trigger conditions are met, the specific content is then read (Anthropic Engineering, Claude Platform Docs). This progressive loading reduces context cost and allows skills to carry arbitrarily complex code or documentation (Anthropic Engineering). In Claude Code, skills can be installed directly into the file system and managed through commands such as /plugins or npx skills add (Tencent Cloud Developer Community, awesome-claude-code-skills). Anthropic’s official documentation also reminds users to use skills only from trusted sources to prevent malicious instructions or data leakage (Claude Platform Docs).

Detailed Description of Core Skills

The following sections explain each skill by type, supplemented with sample code and related resources.

Brainstorming

Function: Force the AI to think and clarify requirements before starting to code. This skill guides Claude to first raise the core questions, at least three possible solutions and their pros and cons, possible edge cases, and risks (Tencent Cloud Developer Community, obra/superpowers). For example, when adding OAuth2 login to a user module, Claude will list rate-limiting approaches such as token bucket, leaky bucket, and sliding window, and ask about differences in strategy depending on whether the protected target is a database or an API (Tencent Cloud Developer Community). After installation, the system automatically triggers brainstorming when the task involves feature design or creative development. It can also be started manually by typing /brainstorming (Tencent Cloud Developer Community).

# Install the superpowers brainstorming skill, CLI example
npx skills add obra/superpowers@brainstorming

# Invoke it with the Claude Code CLI
claude <<EOF
/brainstorming I want to implement a new search feature
EOF

In the example above, Claude will first produce a structured analysis report, including comparisons among multiple solutions and a clear recommendation (Tencent Cloud Developer Community). Because this skill leans toward logical reasoning, it may feel verbose in simple tasks. You can skip it by adding instruction text, such as “small change, execute directly without brainstorming” (Tencent Cloud Developer Community). Anthropic’s open-source framework obra/superpowers provides the corresponding Skill template, and the Chinese enhanced version also fully translates this skill (superpowers-zh).

Writing Plans

Function: Break a complex requirement into ordered, executable steps. Claude outputs a detailed implementation plan, including 5–10 clearly verifiable action steps, the expected output of each step, dependencies between steps, and assumptions that need confirmation (obra/superpowers, Tencent Cloud Developer Community). For example, for “add gRPC support to an existing REST API,” Claude lists seven steps: analyze interfaces, define .proto, generate code, implement services, map errors, write tests, and update documentation (Tencent Cloud Developer Community). The usage is to add /writing-plans in the conversation, either automatically or manually, so that Claude aligns on direction before taking action.

# Example of invoking the writing-plans skill in Python
from claude_agent_sdk import query

async for msg in query(prompt="/writing-plans Add gRPC support to the existing REST API"):
    print(msg.content.text)

Through this skill, developers can review the plan before implementation and discover missing steps in advance, such as step order or dependencies (Tencent Cloud Developer Community). The obra/superpowers framework already includes an implementation of the writing-plans skill, and the community also provides corresponding documentation. When using it, note that the plan generated by this skill still needs interactive confirmation and cannot fully replace human thinking.

Executing Plans

Function: Execute a previous plan step by step and verify the result after each step. This skill requires Claude to check, after completing each step, whether the expected output has been verified, such as tests passing, files being generated, or commands succeeding, before moving to the next step (obra/superpowers, Tencent Cloud Developer Community). If a step fails, Claude stops and reports the problem, then waits for human instructions (Tencent Cloud Developer Community). This prevents Claude from “working around” or skipping problems, ensuring that the whole process remains reliable. For example, the plan generated earlier can be pasted into /executing-plans for execution.

# Execute a plan with the CLI, example
claude <<EOF
/executing-plans
1. Analyze the existing API interface list
2. Define the proto file
...  # Paste the plan output from writing-plans here
EOF

Together with writing-plans, this is a commonly used combination (Tencent Cloud Developer Community). Anthropic’s official documentation also points out that structured workflows can prevent damaged results (Claude Platform Docs). However, this skill increases the number of verification steps, and for multi-stage tasks it may add interaction cost and latency.

Test-Driven Development

Function: Force the use of TDD, writing tests before writing code. After being triggered, Claude first refuses to directly write implementation code. Instead, it asks about user stories, success criteria, and edge cases (obra/superpowers, Tencent Cloud Developer Community). It then first generates corresponding test cases and asks the user to confirm them, before writing implementation code that passes those tests (Tencent Cloud Developer Community). This avoids the common problem in which tests written afterward merely test the implementation rather than the business requirements (Tencent Cloud Developer Community).

# TDD invocation example
async for msg in query(prompt="/test-driven-development Implement the redemption function of a user points system"):
    print(msg.content.text)

Example comparisons show that without TDD, tests added later often only target implementation logic. With the TDD Skill enabled, tests align directly with business behavior, so even if the implementation is rewritten, the tests still ensure functional correctness (Tencent Cloud Developer Community). In obra/superpowers, TDD is part of the enforced workflow. When using it, you can configure certain directories in CLAUDE.md to enforce TDD throughout the process, avoiding the need to manually trigger it every time (Tencent Cloud Developer Community).

Systematic Debugging

Function: Debug errors through a four-stage systematic process: observe → hypothesize → test → fix (obra/superpowers, Tencent Cloud Developer Community). When an error occurs, Claude sequentially asks for a description of the phenomenon and reproduction conditions, proposes 3–5 possible root-cause hypotheses ranked by testability, designs the smallest verification step for each hypothesis, such as adding logs or unit tests, then identifies the root cause and proposes a fix (Tencent Cloud Developer Community). For example, when investigating intermittent 504 errors in an API, observing that errors only occurred on Wednesday afternoons narrowed the search scope and revealed a root cause: conflict with a scheduled task. If one simply “adds a timeout,” the problem is hidden rather than solved (Tencent Cloud Developer Community).

# Example of triggering the systematic-debugging skill
claude <<EOF
/systematic-debugging
Symptom: the order API occasionally returns 504 errors, with a frequency of about 1%, concentrated on weekday afternoons
EOF

This skill is a methodology designed specifically for debugging (Tencent Cloud Developer Community). Anthropic’s developer guide also emphasizes that skills need clear outputs and workflows in order to execute reliably (The Complete Guide to Building Skills for Claude). It is worth noting that although systematic debugging formalizes the debugging thought process, if the initial observation information is insufficient or the hypotheses are inaccurate, developers still need to adjust the input and verification strategy at the right time.

Requesting Code Review

Function: Invoke multiple expert agents in parallel to automatically review code. After being triggered, Claude simultaneously creates five sub-agents, respectively responsible for security checks, performance checks, correctness checks, code style review, and test coverage checks (obra/superpowers, Tencent Cloud Developer Community). Each sub-agent analyzes the code segment, and the final result is summarized into a review report containing issue locations and high/medium/low confidence labels (Tencent Cloud Developer Community). For example, one review found vulnerabilities in a payment module: the security agent reported missing IP whitelist validation, while the correctness agent reported a concurrency race condition (Tencent Cloud Developer Community).

# Code review request example
claude <<EOF
/requesting-code-review
Focus especially on concurrency safety and idempotency
EOF

This skill is highly useful for long development sessions, but it also introduces performance overhead from multiple parallel queries. Anthropic’s developer guide mentions that skill execution issues need attention (The Complete Guide to Building Skills for Claude). In practice, it can be combined with writing-plans and used only before critical PRs or merges, balancing speed and quality. The core of obra/superpowers already includes this multi-agent review logic.

Dispatching Parallel Agents

Function: Process independent tasks that have no dependency relationship in parallel, accelerating development. Once enabled, Claude automatically identifies independent subtasks in the requirement, creates a new agent for each one, executes them simultaneously, and merges the results after completion (obra/superpowers, Tencent Cloud Developer Community). For example, when adding the same feature or refactoring across multiple microservices, serial execution may take dozens of minutes, while parallel agents can work simultaneously and significantly reduce total time (Tencent Cloud Developer Community).

# Parallel agents example
claude <<EOF
/dispatching-parallel-agents
I need to add unified logging middleware to the following 6 microservices:
user-service, order-service, payment-service, notification-service, inventory-service, audit-service.
Each service is independent and can be processed in parallel.
EOF

Note that each subtask must be self-contained and must not depend on the others, meaning there should be no shared state (Tencent Cloud Developer Community). If dependencies exist, the earlier combination of writing plans plus executing plans should be used instead. Anthropic’s official documentation also mentions that skills can include code-execution tools, but it does not specifically demonstrate this workflow. In practice, pay attention to the additional demands on context and computing resources.

Verification Before Completion

Function: Before Claude reports that something is “complete,” force it to execute a verification checklist to ensure that real completion includes tests, security checks, and other validations (Claude Platform Docs, Tencent Cloud Developer Community). The checklist includes whether unit tests passed, whether hard-coded values should be extracted into configuration, whether error handling is complete, whether security risks were introduced, and whether documentation/configuration was updated (Tencent Cloud Developer Community). After this skill is enabled, the completion report lists the result of each check, using marks such as ✅ or ❌, giving developers a clear picture of remaining issues before committing code (Tencent Cloud Developer Community).

# Verification before completion example, CLI
claude <<EOF
/verification-before-completion
EOF

In general, this skill automatically triggers at the end of every task, because it is already configured in the superpowers rules. It can also be invoked manually when needed (Tencent Cloud Developer Community). Note that after enabling it, every completion must go through the full checklist, which may lengthen the interaction process, but it can greatly reduce omissions and technical debt.

Using Git Worktrees

Function: Create isolated development-branch workspaces. This skill automatically creates a separate worktree branch in the repository for each feature, switches to a new branch there for development, and after completion provides a standardized merge/PR/abandon workflow (obra/superpowers, Tencent Cloud Developer Community). This means the main repository directory is not affected by changes from the new feature, greatly reducing the hassle of stash and branch management (Tencent Cloud Developer Community).

# Git Worktree example
claude <<EOF
/using-git-worktrees Start developing the user notification feature
EOF

After execution, Claude automatically creates a new worktree under .claude/ and switches branches (Tencent Cloud Developer Community). This avoids the conflict risk caused by frequently using stash in a traditional single working directory (Tencent Cloud Developer Community). This skill effectively combines commands such as git worktree add with development workflow conventions, so users do not need to manually remember complex parameters. Note that this process requires write permission to the current Git repository, and users need to understand basic Git branch-management concepts.

Excalidraw Diagram

Function: Generate editable Excalidraw diagrams from natural-language descriptions, such as architecture diagrams, flowcharts, sequence diagrams, ER diagrams, and so on (coleam00/excalidraw-diagram-skill, Tencent Cloud Developer Community). Users only need to describe the diagram they want in text. Claude then generates a .excalidraw JSON file, which can be opened in the Excalidraw desktop app or browser plugin and edited by dragging elements around (Tencent Cloud Developer Community). Compared with Mermaid, which is difficult to modify once generated, Excalidraw has clear advantages in editability and visualization (Tencent Cloud Developer Community).

# Excalidraw diagram example
claude <<EOF
/excalidraw-diagram
Draw an architecture diagram for an e-commerce order system, including:
user service, order service, payment service, inventory service, and message queue Kafka.
EOF

After running, a .excalidraw file is generated in the current directory (Tencent Cloud Developer Community). Claude can also assist with layout and check overlap issues. As the skill README describes, it can use Playwright rendering checks (coleam00/excalidraw-diagram-skill). This skill requires installing additional tools, such as a Node.js MCP server and related toolchain, or following the guide in the coleam00 repository or yctimlin/mcp_excalidraw. Even so, for scenarios that require quickly generating architecture diagrams and then manually polishing them, it is highly efficient.

Comparison Table of Implementation Sources

Skill Name	Official / Community Implementation	Example / Reference	Limitations and Differences
Brainstorming	obra/superpowers, superpowers-zh	Supports /brainstorming syntax (Tencent Cloud Developer Community)	Community skill, no exact official equivalent. Can be disabled for simple requirements to avoid verbosity. The guidance is relatively fixed.
Writing Plans	obra/superpowers	/writing-plans command format (Tencent Cloud Developer Community)	Same as above. Generated plans depend on input quality. If requirements are unclear, plans may be incomplete.
Executing Plans	obra/superpowers	Execute with /executing-plans by pasting the plan (Tencent Cloud Developer Community)	Same as above. Adds interaction count and execution time. Developers need to watch for interruption when errors occur.
Test-Driven Development	obra/superpowers	/test-driven-development command (Tencent Cloud Developer Community)	Same as above. Requires the model to understand TDD basics. Test quality depends on skill rules. May take longer than direct coding.
Systematic Debugging	obra/superpowers	/systematic-debugging plus error description (Tencent Cloud Developer Community)	Same as above. Requires complete error context. If key logs are missing, the effect is limited.
Requesting Code Review	obra/superpowers	/requesting-code-review (Tencent Cloud Developer Community)	Same as above. Parallel multi-agent review greatly increases latency and API calls. The model may produce false positives, though confidence labels help.
Dispatching Parallel Agents	obra/superpowers	/dispatching-parallel-agents (Tencent Cloud Developer Community)	Same as above. Subtasks must not share state and task descriptions must be self-contained. Poor decomposition makes it fail. Parallel overhead is high.
Verification Before Completion	obra/superpowers, technical principle also reflected in official docs (Claude Platform Docs)	/verification-before-completion (Tencent Cloud Developer Community)	Same as above. Every completion is forced through checks, increasing interaction. Rules depend on skill definitions, so the checklist must remain comprehensive and up to date.
Git Worktrees	obra/superpowers	/using-git-worktrees (Tencent Cloud Developer Community)	Same as above. Requires familiarity with Git. Requires local Git worktree support. Large repositories may be slow.
Excalidraw Diagram	Official skill or community repository such as coleam00/excalidraw-diagram-skill	/excalidraw-diagram (Tencent Cloud Developer Community)	Official or community plugin. Requires installing frontend rendering tools. Generates editable JSON files. Sensitive to network and dependency environment.

Learning Path and Practical Recommendations

Based on skill complexity and application value, it is recommended to master them gradually in the following order:

1. Workflow awareness: brainstorming and writing plans. First understand how to use brainstorming to clarify requirements and writing plans to decompose tasks (Tencent Cloud Developer Community). Practical exercise: choose a relatively complex feature requirement, such as a new user-registration flow. First use /brainstorming to generate requirement analysis, then use /writing-plans to formulate the implementation plan.

2. Core implementation: executing plans and TDD. Learn to execute step by step according to the plan and self-check errors, while also building the habit of test-driven development (Tencent Cloud Developer Community). Exercise: use a small project to practice TDD. First let Claude generate tests with /test-driven-development, then implement the feature. Also use /executing-plans to complete the plan created earlier.

3. Debugging and verification: systematic debugging and verification before completion. Master the four-stage debugging workflow to fight errors, and force a verification checklist before the end of every task (Tencent Cloud Developer Community). Choose sample code with known bugs and use /systematic-debugging to investigate. At the same time, invoke /verification-before-completion after every development task to check for omissions.

4. Team collaboration: requesting code review and parallel agents. Learn more advanced automation for code review and task parallelization. After making a simple code submission, use /requesting-code-review to obtain a report and understand the meaning of confidence levels in the report (Tencent Cloud Developer Community). Then design a case that can be split into subtasks, such as updating multiple module configurations at the same time, and use /dispatching-parallel-agents to accelerate processing. Pay attention to the dependency condition of parallel logic: subtasks must not depend on each other.

5. Tools and diagrams: Git Worktrees and Excalidraw. Finally, learn skills that improve the development workflow. Use /using-git-worktrees to create parallel branch workspaces (Tencent Cloud Developer Community). Practice independent development in multiple terminals without interference. For architecture design, use /excalidraw-diagram to automatically generate system diagrams, then fine-tune them in Excalidraw. A shopping-cart system or microservice architecture can be used as an exercise, letting Claude help draw the diagram and debug the format (Tencent Cloud Developer Community, coleam00/excalidraw-diagram-skill).

In practice, the skills above can be chained into a development workflow: first use brainstorming and writing plans to determine the solution, then use executing plans to code, use systematic debugging when errors occur, use TDD for tests, run the verification checklist after completion, and finally request code review or run multiple tasks in parallel. Each stage can be paired with its corresponding skill. Developers are encouraged to read the Skill files during practice and refer to open-source implementations such as obra/superpowers and superpowers-zh to understand the details.

Risks and Mitigation Measures

• Security and privacy: Skills contain executable instructions and tool calls, which can be maliciously written to perform dangerous operations. Anthropic explicitly warns users to use only skills from trusted sources and recommends fully reviewing every file in a skill, including SKILL.md and scripts (Claude Platform Docs). If third-party skills must be used, be sure to check whether they contain abnormal external requests or system operations to prevent data leakage or system compromise.

• Mistriggering and latency: Automatic triggering of each skill depends on semantic matching. Anthropic’s guide mentions that over-triggering wastes time, while under-triggering reduces effectiveness (The Complete Guide to Building Skills for Claude). Developers can control triggering by adding explicit instructions in the conversation, such as “skip brainstorming.” Too many skills may cause Claude to load context more slowly and increase response latency. Mitigation methods include uninstalling unnecessary skills when they are not needed, or using CLAUDE.md to configure disabling rules.

• Dependencies and limitations: Some skills, such as Git Worktrees and Excalidraw, depend on local tools or environment support. For example, Git Worktrees requires git to be installed and the current repository to be initialized. Excalidraw requires starting an additional local canvas server (yctimlin/mcp_excalidraw). If the environment does not match, configure tools first or switch to alternatives such as manual diagramming or traditional Git operations.

• Performance and cost: Parallel agents and review skills launch multiple simultaneous queries, resulting in high computational overhead and potentially consuming more API calls and latency. They should be used only when necessary, especially for high-priority tasks. For non-critical tasks, a simplified workflow can be used.

• Model reliability: Although Skills provide workflow guidance, Claude may still produce inconsistent responses. Anthropic points out that if problems such as inconsistent results or user corrections occur, instructions should be improved or error handling should be added (The Complete Guide to Building Skills for Claude). Developers should verify Skill outputs and gradually tune Skill language or settings to improve accuracy.

Conclusion: Claude Code’s Skill framework makes development workflows programmable, but it is not a replacement for human thinking. Properly combining the skills above can greatly improve development efficiency and quality, but auditing and verification remain necessary. The skills and practical path described in this article can serve as a guide for developers to gradually become familiar with agentic programming methodology (Tencent Cloud Developer Community, Claude Platform Docs).