In a nutshell: A Claude Skill is more like “letting the model know how,” while an OpenClaw Skill is more like “letting the system manage.”

I wanted an AI to write this article, not because the word “Skill” is new, but because I’ve been visiting partners and clients recently and have a subtle feeling that the Chinese market is starting to repeat the same old story with “agents.”

Personally, I believe OpenClaw’s impact and significance for China’s B2B software are more critical. Essentially:

The dynamic of “people who can use AI replacing those who can’t” has shifted to “people who can manage Agents replacing those who can’t.”

The following content, primarily written by an AI, compares the Skill capabilities and mechanisms of the Claude and OpenClaw platforms. However, I believe the B2B industry might be facing more fundamental changes in its software development and application supply chain. The AI’s analysis is still quite superficial, so I won’t go into that today.

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Over the past few years, the concept of “agent” has been overused in China. Many companies claim to be building Agents while merely rebranding workflows, multi-turn conversations, tool calls, or even just simple Q&A wrappers as “agents.” When a concept gets hot, its definition expands; when the definition expands, the market becomes distorted. In the end, those genuinely building solid capabilities are overlooked, while those best at packaging concepts dominate the conversation.

Today, when many teams talk about “Skills,” they aren’t discussing how to consolidate a professional capability into a reusable, callable, and governable unit. Instead, they’re using it as a new buzzword. What they were once hesitant to keep calling an “Agent” is now a “Skill.” What was just a prompt template is now a “Skill.” What was merely a layer of tool orchestration is also a “Skill.” The result is that the concept is being hyped up again, but the industry’s understanding has only become more chaotic.

That’s why I wanted to write this article—not to add more fuel to the fire around the word “Skill,” but quite the opposite. I want to pull it back down to earth and examine it within the boundaries of capability and system architecture.

Though they are both called “Skills,” what Claude and OpenClaw refer to are not the same thing.

1. Don’t rush to ask which is more advanced; first, look at what problems they are each trying to solve. Link to heading

The problem Claude aims to solve is, fundamentally: how to turn a reusable professional capability into a workflow unit that a model can automatically discover and invoke.

This is why the official Anthropic documentation repeatedly emphasizes several points: first, a Skill is a modular capability; second, Claude will automatically use it when a request is relevant; and third, it uses a tiered, on-demand loading approach. The model is first made aware of available Skills, and only after one is triggered does it read the SKILL.md and additional resources, thereby reducing context consumption. Claude also explicitly organizes Skill content into three levels: metadata, the main description, and additional resources/code.

In other words, a Claude Skill is more like a form of “capability packaging.” Its focus isn’t on “writing longer prompts” but on organizing “when to trigger, what to read, how to reuse, and how to reduce context pollution” into a capability object that the model can reliably invoke.

The problem OpenClaw aims to solve is more aligned with platform engineering: how to make an Agent’s capabilities into modules that are installable, configurable, filterable, updatable, synchronizable, and distributable.

In the OpenClaw documentation, the most prominent feature isn’t the prompt but the runtime mechanism: Skills are loaded from three levels—the built-in directory, the user directory, and the workspace directory—with clear priorities for resolving conflicts. They can also be extended through additional directories and are filtered at load time based on conditions like the operating system, the existence of binaries, environment variables, and configuration settings.

This shows that an OpenClaw Skill is no longer just about “how a model learns to do something,” but “how a platform incorporates a capability into its governance system.”

2. The real difference isn’t in the file structure, but in the system boundaries. Link to heading

On the surface, Claude and OpenClaw Skills do look very similar.

Both emphasize SKILL.md; both emphasize the description; and neither treats a Skill as a simple prompt, but rather as a capability package with metadata, instructions, and resources. Claude’s official documentation requires Skills to use YAML frontmatter to describe their name and purpose, triggering automatically when relevant. OpenClaw also explicitly states that it follows the AgentSkills layout and intent.

But what truly makes them different isn’t the similarity of their directory structures, but their completely different system boundaries.

Claude’s boundary is primarily on the model side. It is concerned with: When should this capability be used by the model? Once used, what should the model read? How can untriggered content be kept in the file system without occupying context?

OpenClaw’s boundary is primarily on the platform side. It is concerned with: Where is this capability loaded from? Does it meet the runtime conditions? Should it be included in the current run? Should an env or apiKey be injected? Should it be exposed only to user commands? Can it bypass the model and go directly to a tool? Can it be searched, installed, updated, and published through a registry?

Therefore, although both are called “Skill,” they are not abstracting the same object: Claude abstracts “how a capability is invoked by the model,” while OpenClaw abstracts “how a capability is loaded, governed, and distributed by the platform.”

3. A Chart to Understand: The Fundamental Differences Between Claude Skill and OpenClaw Skill Link to heading

The factual basis for this table is straightforward: The official Claude documentation emphasizes automatic relevance-based triggers, file-system-based skills, and on-demand loading. In contrast, the official OpenClaw documentation highlights AgentSkills compatibility, directory priorities, pre-run filtering, command exposure, environment injection, and ClawHub distribution.

So, while both are called “Skill,” Claude and OpenClaw are not abstracting the same concept. This isn’t a terminological difference; it’s a product roadmap divergence.

4. Concrete Scenarios Make the Difference Clearer Link to heading

Scenario 1: Creating a Weekly Client Report PPT for a Bank Link to heading

Imagine a salesperson says: “Help me organize this week’s progress with my banking clients into a presentation.”

In the Claude context, the process would be: The system has a pre-existing “Create PPT” Skill. Claude first examines the skill’s description to determine its relevance to the request. If it matches, Claude reads the SKILL.md file and uses the specified templates, scripts, and resources to accomplish the task.

In the OpenClaw context, the process is different: The platform first checks if the “Create PPT” Skill is installed, its directory level, if it meets all runtime conditions, whether it’s disabled, if an API Key needs to be injected, and if it’s exposed as a slash command. Only after these checks does it decide whether the Skill is eligible for the current agent run.

Therefore, for the same “Create PPT” Skill, Claude’s approach answers the question, “How does the model learn this task?” while OpenClaw’s approach answers, “How does the system package, manage, and distribute this capability?”

Scenario 2: Creating a “Bid Proposal Response” Skill Link to heading

For instance, a fintech company wants to turn its workflow—“read tender document, extract requirements, match with product capabilities, generate initial draft”—into a reusable Skill.

In the Claude context, this would be like creating an “organizational knowledge pack.” You would place the workflow, guidelines, best-practice examples, templates, and auxiliary scripts into the Skill directory, enabling Claude to automatically use them for relevant tasks.

In the OpenClaw context, the platform team would focus on a host of runtime questions: Is this Skill globally shared or workspace-specific? Should it be located in <workspace>/skills or ~/.openclaw/skills? Should it be loaded via extraDirs? Does it need a private enterprise API key injected? Should it be invoked automatically by the model or exposed as an explicit command for the pre-sales team? So the difference is: Claude focuses on encapsulating professional practices for the model; OpenClaw focuses on integrating enterprise capabilities into the platform’s runtime system.

Scenario 3: Customer Service Operations Team Creating a “QA Analysis Skill” Link to heading

For another example, a customer service manager might say: “Perform sentiment analysis, compliance checks, and suggest improvements for yesterday’s 500 call recordings.”

With Claude, the most natural approach is to encapsulate the quality inspection rules, scoring criteria, tagging system, and output format requirements into a Skill. This allows Claude to automatically apply this methodology when a QA task arises. Here, a Skill is more like a “business expert package.”

With OpenClaw, beyond the rules themselves, the platform also considers: Does this Skill depend on external tools or binaries? Does it require environment variables? Should it run on the host machine or in a Docker sandbox? If in a sandbox, how should it be configured, since the host’s environment variables aren’t inherited by default?

This is why I say: Claude’s Skill is more like a capability specification + an instruction manual; OpenClaw’s Skill is more like a capability package + a runtime plugin.

Scenario 4: Exposing Skills as Explicit Commands for Frontline Teams Link to heading

Not all capabilities are suitable for “letting the model decide when to use them.” Some capabilities are meant to be explicitly triggered by the user.

In the Claude ecosystem, slash commands are an entry point, but the focus remains on whether the model will invoke the relevant capability at the appropriate time. The Claude SDK also supports custom slash commands, but they are a related yet distinct mechanism from Skills.

In the OpenClaw ecosystem, slash commands are distinctly more platform-oriented. A user-invocable Skill can be exposed as a command. Default commands can still be handled by the model, but if a Skill declares command-dispatch: tool, it can bypass the model and follow a deterministic tool path directly.

The underlying philosophical difference is significant: Claude is saying that a capability can be both invoked by a user and recalled by the model. OpenClaw is saying that, in addition to being used by the model, a capability can also become part of the platform’s command system and tool gateway.

V. What are the real inspirations from Claude’s Skills and OpenClaw’s Skills for B2B Software? Link to heading

1) Software that is “knowledge-intensive, judgment-intensive, and has non-deterministic workflows” is better suited for Claude-style Skills Link to heading

If a software’s core value lies not in clicking buttons for the user, but in applying professional knowledge, industry experience, templates, and judgment frameworks on their behalf, then it is better suited to follow Claude’s path.

For example, these scenarios are a good fit:

· Finance/Government & Enterprise Pre-sales: Responding to bids, writing proposals, summarizing client visit notes, and competitor analysis.

· Customer Service Operations: Quality assurance analysis, conversation reviews, agent coaching recommendations, and service strategy generation.

· Data Analysis Products: Evolving from “reporting tools” to “business assistants that can analyze data.”

· Legal/Compliance Products: Reviewing initial contract drafts, comparing clauses, and generating compliance checklists.

· Enterprise Knowledge Products: Truly transforming SOPs, case studies, and best practices into work packages that a model can invoke.

The common thread in these scenarios is that the tasks are not entirely deterministic, but professional methodology is crucial.

Claude’s Skill mechanism is well-suited for this type of software because it is naturally designed to accumulate domain knowledge, templates, scripts, and best practices, allowing the model to use them on-demand for relevant tasks, rather than relying on someone to manually copy and paste a prompt each time.

If a B2B software company is better suited to this path, it typically needs to make three types of product changes: First, reorganize the experience scattered across implementation documents, training manuals, and pre-sales templates into capability packages. Second, enable the model with a mechanism to “automatically recall” this experience. Third, establish an evaluation system centered around these Skills.

2) Software that is “integration-intensive, permission-sensitive, and has highly deterministic processes” is better suited for OpenClaw-style Skills Link to heading

If a software’s core value lies in its need to connect to many systems, invoke numerous tools, handle various permissions and runtime dependencies, and where many operations are best executed deterministically, then it is better suited to follow OpenClaw’s path.

For instance, these scenarios align more closely with OpenClaw’s philosophy:

· Enterprise Operations Workbench: Unified operations across CRM, ERP, ticketing, IM, calendar, and email.

· DevOps / IT Automation Platform: Alert handling, script execution, change management, and inspection routines.

· Internal Office Assistant Platform: Explicit commands to trigger leave requests, expense reports, tickets, scheduling, and approvals.

· Multi-team Collaboration Platform: Assembling different capability packages for different departments, tenants, and workspaces.

· ISV Ecosystem Platform: Enabling partners to publish, install, upgrade, and roll back various capability extensions.

The common thread in these scenarios is that capabilities must not only be “understood” but also “governed.”

The reason OpenClaw’s Skills are more like a plugin system is that they directly address the most challenging problems in enterprise software within the Skill itself: dependency existence, environment variable injection, capability visibility, whether it’s invoked by the model or a user command, whether it can directly use a tool, and how to handle installation, updates, and synchronization. If a to-B software company is better suited for this path, then typically four types of changes need to be made to the product: First, capabilities must be abstracted into installable, versionable, and configurable runtime units; second, there must be a clear capability assembly layer; third, there must be a governance layer; and fourth, there must be a distribution layer.

3) Most Mature to-B Software in the Future Will Evolve Towards a “Dual-Layer Skill Architecture” Link to heading

My own judgment is that most mature to-B software in the future will not solely choose either the Claude-style or OpenClaw-style approach, but will form a dual-layer structure: the upper layer will be Claude-style Skills, responsible for endowing models with domain understanding, method invocation, and content generation capabilities; the lower layer will be OpenClaw-style Skills, responsible for managing tools, systems, permissions, environments, and distribution governance.

That is to say: the upper layer solves “whether it can do it”; the lower layer solves “can it do it, is it stable, is it controllable.” Only when these two layers are stacked together does it truly resemble mature enterprise AI software.

For example, a financial industry AICC product, looking up, needs expert capabilities like “Complaint Analysis Skill,” “Quality Inspection Review Skill,” and “Marketing Strategy Skill”; looking down, it must handle platform-level issues such as CRM, work orders, call recordings, knowledge bases, permissions, approvals, and tenant isolation. The former is more like Claude-style Skills, while the latter is more like OpenClaw-style Skills.

4) For domestic to-B software vendors, the real challenge is not “whether they can talk about Skills,” but whether the organization needs to be restructured Link to heading

Ultimately, this is not just about adding a new term to a product.

If you genuinely want to build software into a Skill-driven product, at least three things need to change organizationally: First, the way products are defined must change; second, the delivery method must change; and third, the business model may also need to change.

Once Skills truly become capability units, they are not just deliverables, but can also become value-added packages, industry packages, partner packages, and market packages. At that time, what is sold is not just licenses, but capability assets.

Six, Why This Matters: Skill is Evolving from Prompt Asset to Runtime Asset Link to heading

Many people today talk about Skills, still stuck at “is it a more advanced prompt template.”

This actually underestimates it.

If it were just a template, it would at most solve the problem of “reusing textual descriptions”; but from Claude to OpenClaw, this concept has been advancing. Claude turned Skills into professional capabilities that models can discover, load on demand, and reuse; OpenClaw further transformed Skills into installable, configurable, filterable, updatable, synchronizable, and distributable runtime units.

This means that the value of Skills is changing.

In the past, an organization’s method for accumulating AI experience was more about saving prompts, writing SOPs, and building knowledge bases; now, Skills attempt to transform these experiences into capability objects that the system can truly invoke, load, govern, and reuse. It is no longer just a documentation asset, but begins to resemble a software asset.

From this perspective, Claude and OpenClaw are not about who is right or wrong, but rather are on the same evolutionary curve, just stopped at different positions: Claude is closer to the model-side capability encapsulation; OpenClaw is closer to the platform-side capability operations.

Seven, What’s Truly Worth Alerting to, is Not That Skill Has Become Popular, But That Skill is About to Be Overused Again Link to heading

Today, many people in the market treat Skill as a new buzzword after Agent, but what is truly worth paying attention to is not whether the name has changed, but whether the boundaries of the capability unit have changed.

If a so-called Skill cannot improve the stable performance of a model in certain tasks, nor can it be loaded, governed, and distributed by the system, then it is likely just a rebranded prompt, workflow, or demo shell.

This is also what I truly want to remind the market: Skill is not a more fashionable word; Skill should be a more serious capability encapsulation.

If we end up just overusing the word Agent, and then overusing Skill again, then the industry has not progressed; it has just put on a new fig leaf.

Eight, Final Judgment Link to heading

If I had to summarize this article in one sentence, I would write it this way: The focus of Claude Skill is to enable models to reuse a capability more stably; the focus of OpenClaw Skill is to enable platforms to govern a capability more systematically.

Therefore, what is truly worth paying attention to in this discussion is not “which product also uses the term Skill,” but rather: Skill is evolving from “a way to reuse model prompts” to “a capability encapsulation and distribution unit in the Agent era.”

The former leans towards capability packaging, and the latter leans towards capability operations; the former is more about defining “how to make the model capable,” and the latter is more about defining “how to make the system manage.”

This is where the concept of Skill truly has value. And this is why today we must quickly pull it back from the hype and put it back into the context of capability building and system building.

References Link to heading

1. Anthropic, Agent Skills Overview — https://platform.claude.com/docs/zh-CN/agents-and-tools/agent-skills/overview

2. Anthropic, Agent SDK Slash Commands — https://platform.claude.com/docs/en/agent-sdk/slash-commands

3. OpenClaw, Skills — https://docs.openclaw.ai/en/tools/skills

4. OpenClaw, Skills Config — https://docs.openclaw.ai/en/tools/skills-config

5. OpenClaw, ClawHub — https://docs.openclaw.ai/en/tools/clawhub