Skool MCP
Skool MCP
让 Claude 访问你的 Skool 社区。帖子、评论、成员、课堂以及你的 DM 收件箱。
你可以问 Claude 诸如“这周大家发了什么帖子?”、“起草对最近 5 条 DM 的回复”,或者“把我的成员列表拉进电子表格”。它运行在你的电脑上,使用你自己的 Skool 登录。
非官方。不是 Skool 构建的,也与 Skool 无关联。
你能用它做什么
13 个工具。读取类的可以放心使用。写入类的会以你的名义公开发布,所以 Claude 应该先与你确认措辞。
Tool | What it does | Read or write |
| 确认你的 Skool 登录有效,并列出你所属的社区。出问题时先运行这个。 | 读取 |
| 列出你社区动态中的最近帖子:标题、摘要、评论数和点赞数、作者。 | 读取 |
| 读取一篇完整帖子及其评论。 | 读取 |
| 向你的社区动态发布新帖子。 | 写入 |
| 给帖子添加评论。 | 写入 |
| 列出你社区的成员:id、姓名、邮箱、简短简介。 | 读取 |
| 列出你社区中的课堂课程。 | 读取 |
| 读取课程的模块和课时,以及某一课的内容。 | 读取 |
| 你的 DM 收件箱:未读数和最后一条消息的预览。 | 读取 |
| 读取一个 DM 会话中的消息。 | 读取 |
| 向现有会话发送一条 DM。 | 写入 |
| 将 DM 会话标记为已读。 | 写入 |
| 与成员开启新的 DM。 | 写入 |
Related MCP server: kaushik-linkedin-mcp
开始之前
macOS 或 Windows。(Linux 未经测试。)
Claude Code 或 Claude Desktop。
一个 Skool 账号,并且该账号确实是你想连接的社区的成员。
就这些。你不需要安装 Python。安装程序会安装它所需的一切。
安装
第 1 步:把文件夹放到你的电脑上。 两种方式都行。
选项 A:如果你有 git:
cd ~
git clone https://github.com/Solnest-AI/skool-mcp-community.git skool-mcp这会把项目放到 ~/skool-mcp,这正是你想要的位置。
选项 B:ZIP 压缩包:
下载 ZIP(在仓库页面:绿色的 Code 按钮,然后点击 Download ZIP)。
解压。
将文件夹重命名为
skool-mcp,并移动它,使其直接位于你的主文件夹中。
第 2 步:把它放到正确的位置。 这一点比听起来更重要。
Mac:
~/skool-mcp(即/Users/yourname/skool-mcp)Windows:
C:\Users\yourname\skool-mcp
不要放在“Documents”。不要放在“Desktop”。不要放在“Downloads”。macOS 会锁定这些文件夹,试图读取它们的后台任务会以非常难以调试的方式失败。放在主文件夹,搞定。
第 3 步:让 Claude 指向该文件夹,然后说“set this up”。
在 Claude Code 中:
cd ~/skool-mcp
claude然后输入:Set this up.
Claude 会读取 SETUP.md 并运行整个过程:安装工具、打开浏览器让你自己登录 Skool、验证连接、注册服务器,并进行测试。当它需要你时,会停下来询问你。
改为在 Claude Desktop 中设置?同样操作。从 Claude Code(或手动)运行设置,在注册步骤告诉 Claude 你想在 Claude Desktop 中使用它。
这是如何运作的,以及你需要知道什么
请阅读这一部分。它很短,而且是实话实说的版本。
Skool 没有官方 API。 没有开发者计划,没有 API 密钥,也没有受支持的接入方式。所以这个工具做的是你的浏览器所做的事:它使用你自己已登录的会话,与 Skool 网站使用的相同内部端点通信。
你的登录信息只留在你的机器上。 在设置过程中,会打开一个真实的浏览器窗口,你自己登录 Skool,和平时完全一样(Google 登录和 2FA 都有效)。脚本会从该浏览器中读取会话 cookie,并将其写入一个名为 .env 的本地文件。不会向 Solnest、Anthropic 或任何其他地方发送任何内容。
永远不要把你的 cookie 粘贴到聊天中。 不要给 Claude,不要给我,不要给社区里任何想帮忙的人。那个 cookie 就是你的整个 Skool 账号:你的帖子、你的私信、你的账单、你的成员。任何持有它的人都会以你的身份登录。设置的设计使得 cookie 永远不必出现在对话中,而且 Claude 被指示在你主动提供时拒绝。
.env 就是你的密码文件。 要像对待密码文件一样对待它。不要在屏幕共享中打开它,不要截图,不要粘贴到任何地方,不要放到 Drive 或 Slack 里。这个工具包已经设置好,不会把它包含在你上传的任何代码中,所以你基本上只需要不要特意去分享它。如果你觉得它泄露了,就在所有地方退出 Skool 并重新运行设置。
这些工具会以你的身份操作。 由 skool_create_post 创建的帖子就是你的帖子。DM 来自你。它看起来和你自己输入的一模一样,因为功能上确实如此。在发布任何内容之前,让 Claude 把草稿读给你听。
只在你真正所属的社区上使用它。 这是用你自己的凭据访问你自己的会员身份。别耍小聪明。
Skool 可能会让它失效。 没有官方 API 就意味着没有稳定性承诺。如果 Skool 更改了他们的网站,工具可能会在一夜之间停止工作。当出现问题的时候,先运行诊断程序:
cd ~/skool-mcp
uv run doctor.py它会准确告诉你哪个部分出了问题以及如何修复。它绝不会打印你的 cookie。
你的会话最终会过期。 Skool 登录令牌大约持续一年,所以这种情况很少见。当工具开始出现登录错误时,重新运行 uv run connect_skool.py。
403 是另一个问题,重新登录也无法解决。 Skool 的 API 位于防火墙(AWS WAF)之后,它可能在 Skool 看到请求之前就拒绝你的电脑。发生这种情况时,你的登录完全正常。这个问题有两种版本,需要相反的修复方法:
你的连接指纹。 防火墙会检查连接本身的技术特征,而普通的 Python 看起来不像浏览器。这个工具包现在通过借用 Chrome 的特征自动处理了这一点。更换网络对它没有作用。
你的 IP 地址。 防火墙拒绝你来自的地址,通常是 VPN、代理,或者你与许多人共享的地址。只有更换网络才能解决。
你不必自己判断是哪种情况。运行:
cd ~/skool-mcp
uv run net_check.py它不需要登录,只需五秒钟,就会告诉你属于哪一种以及具体该怎么做。不要一开始就重新连接你的 Skool 登录,那对两种情况都无济于事。
获取帮助
运行 uv run doctor.py(如果遇到任何看起来像 403 或“被阻止”的情况,则运行 uv run net_check.py),然后把输出粘贴给 Claude,请它修复失败的部分。输出可以安全分享:它会打印检查结果、cookie 长度和过期日期,绝不会打印 cookie 本身。
还是卡住了?带着诊断输出发布到社区。不要发布你的 .env。
Available Tools
13 toolsskool_comment_on_postA
Add a comment to a post. post_id is the real post id (the id field from
skool_list_posts/skool_get_post, not the slug). Writes publicly — confirm first.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | ||
| post_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no annotations are provided, the description must convey behavioral traits. It discloses that the operation is a public write ('Writes publicly') and advises confirmation, which is a meaningful caution. It also explains the correct format for `post_id` to avoid errors. This goes beyond a simple statement of the action, though it doesn't mention reversibility or other side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no unnecessary words. The purpose is front-loaded, followed by the parameter clarification and then the behavioral caution. The structure is efficient and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with two required parameters and no output schema, the description covers the purpose, the critical parameter nuance, and the public write nature. It could optionally mention response format, but that's not essential given no output schema. The description is sufficiently complete for an agent to invoke the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 0% schema coverage, the description must clarify parameters. It explicitly clarifies `post_id` by stating it's the real id (from `skool_list_posts`/`skool_get_post`) and not the slug, which is critical for correct invocation. `content` is not described, but it's self-evident from the name and type. The key parameter semantics are addressed well.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action with a specific verb and resource: 'Add a comment to a post.' It also clarifies the ambiguous `post_id` parameter, distinguishing it from the slug, which prevents misuse. This clearly differentiates it from sibling tools like `skool_create_post` (creating a post) and `skool_send_message` (messaging).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides some usage context: it's for commenting on posts, and it warns 'Writes publicly — confirm first,' implying user consent is needed. However, it does not explicitly mention when not to use this tool or how it compares to alternatives like sending messages or creating posts. Guidance is implied but not fully spelled out.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_create_postA
Publish a NEW top-level post to your community feed. Writes publicly — confirm wording with the user first. Returns the new post id.
| Name | Required | Description | Default |
|---|---|---|---|
| title | Yes | ||
| content | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations to rely on, the description fully bears the burden and shines: it explicitly states 'Writes publicly' (a critical side effect), mandates user confirmation, and reveals the return value ('Returns the new post id'). This is exactly the kind of behavioral disclosure needed for a mutation tool.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three tight, front-loaded sentences. The purpose is stated first, followed by the critical write/confirmation note, then the return. Every sentence adds value; there is zero waste. This is a model of concise, structured description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple (2 params, no output schema), and the description covers the key operation, public write behavior, and return. It doesn't mention auth requirements or error conditions, but those are typically inferred for such a straightforward create-and-publish tool. Given the lack of annotations, the description is reasonably complete; a 4 is warranted.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has zero description coverage, and the description doesn't clarify what 'title' and 'content' mean beyond their obvious names. Since the parameters are self-explanatory (a post's title and body), this is acceptable, but the description adds no extra meaning or guidance about constraints or formatting. It's adequate but not more.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb ('Publish') and resource ('NEW top-level post to your community feed'), clearly distinguishing it from siblings like comment or list operations. The phrase 'top-level' explicitly separates it from comment creation, and the tool's intent is unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides good context by specifying it writes publicly and advises confirming wording with the user, which guides when to use it (only after user approval). It doesn't explicitly mention alternatives, but the purpose clarity and sibling names make it obvious when this tool is appropriate. No exclusionary guidance is given, but the behavioral note covers the main usage caveat.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_get_conversationA
Read the messages in one DM conversation (read-only). Get the channel_id from skool_list_conversations. Returns sender, content, timestamp per message.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| channel_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description is the sole source of behavioral info. It discloses the read-only nature and the return shape (sender, content, timestamp). It does not mention rate limits, ordering, or the effect on read state, but 'read-only' reasonably implies no side effects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with purpose and a direct prerequisite. Every sentence adds value, with no wasted words or redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only tool, the description covers the key details: how to get the required parameter and what the return contains. Missing are specifics on limit behavior, ordering, and pagination, but these are not critical for a simple read operation with no output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It explains how to obtain channel_id (via list_conversations) but does not describe the limit parameter at all. The meaning of 'limit' must be inferred from context or its default value.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states a specific action ('Read the messages') on a specific resource ('one DM conversation'), and explicitly marks it as read-only. It also names the sibling tool to obtain the required channel_id, distinguishing it from list_conversations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides a concrete usage step ('Get the channel_id from skool_list_conversations') and implies a context (reading messages, not sending or marking read). It does not explicitly exclude alternatives, but the prerequisite and read-only nature give adequate guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_get_lessonA
Read a classroom course (read-only). course_id from skool_list_courses
returns the course's modules/lessons (id + title). Pass a lesson_id (a child
id) to also pull that lesson's content/metadata (note: many lessons are video-
only, so the text content may be empty).
| Name | Required | Description | Default |
|---|---|---|---|
| course_id | Yes | ||
| lesson_id | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full behavioral burden. It explicitly states the operation is 'read-only', discloses that many lessons are video-only and 'content' may be empty, and indicates what is returned with and without lesson_id. This goes beyond the name and provides essential runtime behavior, though it could mention error handling or response shape in more detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences, front-loaded with the core purpose and read-only nature. The alternative behaviors are explained compactly without fluff, and the video-only caveat is included efficiently. Excellent structure and no wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given there is no output schema, the description adequately describes the return behavior: modules/lessons list (id+title) without lesson_id, and lesson content/metadata with lesson_id, including a caveat about empty content. It covers the essential information for a read-only tool, though it omits potential error conditions or pagination, but these are not critical for basic usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain parameters. It does so effectively: course_id is sourced from skool_list_courses and yields modules/lessons; lesson_id is a child id that triggers content/metadata retrieval. It also warns about empty content. This adds meaning beyond the bare parameter titles, though it doesn't specify formats or constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's primary action ('Read a classroom course'), the resource (course/lesson), and distinguishes it from sibling tools like skool_get_post and skool_get_conversation by focusing on course/lesson content. It also specifies the scope: without lesson_id it returns modules/lessons, with lesson_id it returns lesson content/metadata, avoiding ambiguity.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage context by directing the agent to obtain course_id from skool_list_courses, and explains the optional lesson_id behavior. It implies a typical workflow (list courses → get lesson) but does not explicitly state when to prefer this tool over alternatives like skool_get_post. Still, the guidance is sufficient for correct invocation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_get_postA
Read one full post and (by default) its comments. post_name is the slug
from skool_list_posts (the name field, e.g. 'big-change-...'), not the id.
| Name | Required | Description | Default |
|---|---|---|---|
| post_name | Yes | ||
| with_comments | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It discloses the default behavior of including comments ('by default') and clarifies that post_name is a slug, not an id. However, it does not mention authentication requirements, error handling, or side effects (though as a read, side effects are minimal). This is adequate but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise at two sentences, with the action and scope front-loaded. The parameter clarification is seamlessly integrated into the second sentence without redundant phrasing. Every word earns its place, and the structure aids quick comprehension.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the simplicity (2 params, no output schema) and no annotations, the description covers the essential aspects: what it does, the key parameter nuance, and default behavior. It lacks details on error responses or exact return structure, but for a read tool with a clear resource, it is mostly complete. The mention of 'full post' and 'comments' gives a reasonable picture of the return content.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It adds critical meaning to post_name by clarifying it is a slug from skool_list_posts and not an id, which is essential for correct invocation. It also indirectly explains with_comments via the 'by default' phrasing. This adds significant value beyond the bare schema, though not comprehensive for all params.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Read') and the resource ('one full post' and 'its comments'). It distinguishes from siblings like skool_list_posts (listing) and skool_create_post (creation) by specifying a single post retrieval. The parameter clarification further anchors the purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description indicates when to use this tool by stating it reads one full post, implying it is for single-post retrieval rather than listing. It also references skool_list_posts as the source of post_name, which signals a workflow of listing first then getting details. However, it does not explicitly say when not to use it or name alternatives directly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_list_conversationsA
Your DM inbox (read-only): conversations with channel_id, unread count, and last-message preview. Use a channel_id with skool_get_conversation to read it.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It explicitly states 'read-only', disclosing that this operation has no side effects. It also lists the output contents (channel_id, unread count, preview), giving the agent a sense of what to expect. It does not mention pagination or rate limits, but for a list operation the key safety trait (read-only) is covered.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no wasted words. The main purpose and scope are front-loaded, and the usage hint about get_conversation is placed after the primary info. Structure is clean and efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with one optional parameter and no output schema, the description covers what the tool returns (fields), the scope (DM inbox), safety (read-only), and the natural next step. An agent has enough to invoke it correctly without further ambiguity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has only one parameter (limit) with 0% description coverage, and the description does not mention limit at all. While 'limit' is a common parameter, the description fails to explain its effect (e.g., max number of conversations to return, default 30). Since the description is the only place to compensate for the missing schema documentation, this is a notable gap.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the resource ('DM inbox') and the action (list conversations), and specifies the fields returned (channel_id, unread count, last-message preview). It also distinguishes itself from sibling get_conversation by directing the reader to use it for reading a specific conversation. This is a precise, non-redundant purpose statement.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent to use a returned channel_id with skool_get_conversation for follow-up, which implies this tool is for browsing the inbox before drilling into a conversation. It does not explicitly state when not to use it or alternatives, but the pointer to the sibling tool provides clear context. Given the number of siblings and the clear naming, this is adequate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_list_coursesA
List the classroom courses in your community (read-only): id, title, description. Use a course id with skool_get_lesson to read its lessons.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full behavioral burden. It discloses the key trait of being read-only, which implies no side effects or destructive actions. It also indicates what data will be returned. However, it doesn't mention any potential limitations such as pagination, rate limits, or behavior when no courses exist. For a simple list operation, this is adequate but not comprehensive, so a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is exactly two concise sentences, with the primary action and scope front-loaded. The first sentence states the purpose and return fields, the second gives a clear pointer to the related lesson tool. There is zero wasted wording, and each word earns its place. This is an ideal structure for clarity and scannability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters, no output schema), the description provides all necessary information: what the tool does, the scope, the read-only nature, and the exact fields returned. It also suggests how to proceed with a course id. There is no missing information that would prevent an agent from calling the tool correctly. A slightly higher score would require more detail about return edge cases or error handling, but this is not essential for a simple list operation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema has 100% coverage (trivially, since there are no properties to document). The description adds no parameter explanations because none are needed. The baseline for zero-parameter tools is 4, and the description doesn't attempt to explain anything beyond the absence of parameters, which is correct. No additional semantic value is required or provided, but the baseline is met.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a clear verb ('List'), a specific resource ('classroom courses'), and a scope ('in your community'). It also explicitly marks the operation as 'read-only' and lists the returned fields (id, title, description), fully distinguishing it from sibling tools like list_posts or get_lesson. This is a precise, unambiguous statement of purpose.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description tells the agent when to use this tool (to list courses) and directs it to the related tool (skool_get_lesson) for further action, using a course id. While it doesn't explicitly contrast with other listing tools like skool_list_posts, the domain-specific focus and the natural next-step suggestion provide clear practical guidance. It could be more explicit about alternatives, but the intent is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_list_membersA
List members of your community (read-only): id, name, email, short bio. Use member ids with skool_start_chat to open a DM.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses the read-only nature of the operation, which is a key behavioral trait. Beyond that, it does not mention pagination, how the limit parameter affects results, authentication requirements, or potential errors. With no annotations provided, the description carries the full burden but only partially covers the behavioral aspects.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary action and returned fields, followed by a useful cross-reference to skool_start_chat. Every word contributes value, with no redundancy or filler. The structure is clean and immediately scannable.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with only one parameter and no output schema, the description covers the main purpose, explicitly states the return fields, and offers a practical follow-up action. It is missing an explanation of the limit parameter's behavior and default, but overall it provides enough context for an agent to understand the tool's role and basic use.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The single parameter 'limit' is not mentioned in the description at all, and schema description coverage is 0%. The agent receives no guidance on how limit influences the number of members returned or whether there is a default. The description fails to compensate for the lack of schema documentation, leaving the parameter's meaning entirely up to inference from its name and default.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('List members of your community') and the resource, along with the specific fields returned (id, name, email, short bio). The 'read-only' qualifier distinguishes it from mutation tools, and the resource 'members' differentiates it from sibling list tools like skool_list_posts or skool_list_courses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides one concrete usage context: obtaining member ids for use with skool_start_chat to open a DM. However, it does not explicitly compare with alternative list tools or state when not to use this tool. No exclusions or alternative recommendations are given, leaving some ambiguity for an agent deciding between list tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_list_postsA
List recent posts in your community feed (read-only). Returns each post's
id, name (slug), title, a content snippet, comment/upvote counts, author.
Use the name with skool_get_post to read a full post + its comments.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It discloses the read-only nature, the returned fields (id, name, title, snippet, counts, author), and the 'recent' scoping. It doesn't mention pagination or ordering details, but for a simple list tool this is adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no fluff. The core verb and scope are front-loaded, and the return format and cross-tool hint are placed efficiently. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter list tool with no output schema, the description provides enough: the purpose, return fields, and a pointer to the next step. The missing explanation of `limit` is the main deficiency, but the overall context is sufficient for correct invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not mention the `limit` parameter at all. While 'limit' is a common concept, the tool fails to explain its effect, bounds, or default behavior beyond the schema's default value. This is a notable gap given the low coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb ('List'), a resource ('posts in your community feed'), and explicitly notes it is read-only. It also distinguishes itself from skool_get_post by clarifying that this returns a snippet, not full posts. The purpose is unmistakable and differentiates from the main sibling.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent to use the returned `name` with skool_get_post for full posts, providing a clear routing condition. It does not address other siblings (e.g., list_members, list_courses), but given the post-specific context, the guidance is sufficient for the common case.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_mark_readA
Mark a DM conversation as read. Get the channel_id from skool_list_conversations.
| Name | Required | Description | Default |
|---|---|---|---|
| channel_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full responsibility for disclosing behavioral traits. It only states the action itself ('Mark as read') without detailing side effects, permissions, reversibility, or any response. For a mutation tool, this is insufficient disclosure, particularly regarding what changes and what the result is.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, efficient sentence. The core action is front-loaded, and the only extra information (the source of the parameter) is presented immediately afterward. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is low complexity (one parameter, no output schema), but the description covers only the action and parameter source. It does not mention the response or any side effects, which might be expected for a mutation tool. Given the minimal annotations and schema richness, the description is adequate for invocation but not fully complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It does add value by pointing to the source of the channel_id (skool_list_conversations), which is a helpful hint. However, it does not explain the meaning of 'channel_id' beyond the identifier itself, which is a minor gap for a single parameter.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Mark a DM conversation as read') with a specific verb and resource. It distinguishes itself from siblings by the action type (e.g., get_conversation, send_message). The phrase 'Get the channel_id from skool_list_conversations' adds context and prevents confusion with other conversation tools.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description offers clear context by telling the agent how to obtain the required parameter (from skool_list_conversations). It does not explicitly contrast with alternatives, but the purpose is straightforward enough that exclusions are not critical. This meets the 'clear context, no exclusions' bar.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_send_messageA
Send a DM into an existing conversation. Writes — confirm wording first. Get the channel_id from skool_list_conversations.
| Name | Required | Description | Default |
|---|---|---|---|
| content | Yes | ||
| channel_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It states 'Writes', indicating a state-changing operation, and adds a caution to 'confirm wording first', suggesting irreversibility. However, it does not disclose permissions, rate limits, failure modes, or what happens to the conversation. It provides basic but not comprehensive behavioral context.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, front-loaded with the core action first. The warning follows logically, and the channel_id sourcing is given in a separate sentence. No fluff, every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple 2-parameter operation with no output schema, the description covers the essential prerequisite (obtaining channel_id), the write nature, and a caution. It doesn't mention error scenarios or return values, but for this low complexity, it provides enough for an agent to invoke it correctly. Minor gaps are acceptable given the tool's simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must explain the parameters. It gives a direct source for channel_id (from list_conversations), and content is implicitly understood as the message text from the verb 'Send'. However, it doesn't specify any constraints, formats, or expectations for content, and doesn't explicitly link content to the parameter. It adds some value but falls short of fully clarifying both parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (send a DM), the target (an existing conversation), and the write nature. It distinguishes from starting a new conversation by specifying 'existing', which is a key differentiator from the sibling 'skool_start_chat'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It provides an explicit instruction on how to obtain the channel_id (from skool_list_conversations), which is actionable for the agent. While it doesn't explicitly state when not to use it, the phrase 'existing conversation' implicitly guides away from starting a new chat. This is clear but not fully explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_start_chatA
Open a new DM with a member (by their user_id from skool_list_members). Returns the new conversation so you can then skool_send_message into it.
| Name | Required | Description | Default |
|---|---|---|---|
| user_id | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It covers the core behavior (creates a new DM) and the return value (the conversation), but does not mention side effects, permission requirements, idempotency (whether calling again errors or returns existing), or potential rate limits. It hints at a prerequisite (user_id from skool_list_members) but omits failure scenarios. This is acceptable but not exhaustive.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, tightly worded sentence. It front-loads the primary action and resource, then provides the parameter source, followed by the return value and next step. Every phrase earns its place—no filler, no redundancy. This is an model of concise, structured tool documentation.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with only one parameter, no output schema, and no annotations, the description is relatively complete. It states what it does, what it returns, and how to obtain the input. It also indicates the follow-up action (send_message). Missing are potential error scenarios (e.g., invalid user_id, conversation already exists) and any explicit note that authentication is assumed. These are minor gaps given the simplicity.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Given schema coverage is 0%, the description must add meaning to the single parameter. It does so by specifying the source ('user_id from skool_list_members'), which clarifies that it is the member's identifier from a prior call, not a free-form input. It also implies the parameter is required (which the schema confirms). While it doesn't describe format or validation, the source reference adds significant semantic value beyond the bare schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool's action ('Open a new DM') and the resource (a member via user_id). It distinguishes from siblings like skool_send_message (sends to existing conversation) and skool_list_conversations (lists conversations) by specifying it creates a new conversation. The phrase 'so you can then skool_send_message into it' clarifies the intended downstream use.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is a prerequisite for sending messages to a new member, referencing skool_send_message as the follow-up. It also points to skool_list_members as the source for user_id, giving a clear context. However, it does not explicitly state when NOT to use it (e.g., if a conversation already exists) or contrast with skool_list_conversations as an alternative for existing chats. Thus, it provides clear context but no explicit exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
skool_whoamiA
Confirm the Skool cookie works and list the communities you belong to. Call this first if other tools error — it isolates auth/cookie problems.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It clearly states the two behaviors (cookie check and community listing), implying a read-only operation. It does not mention error handling or response details, but for a whoami-style tool this is largely implied and acceptable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no wasted words. The primary purpose is front-loaded, and the critical usage tip follows immediately. Ideal for a simple tool.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter, no-output-schema tool, the description covers the essential purpose and usage context. It could mention expected output format (e.g., list of community names/IDs) or error behavior, but those are minor gaps given the tool's simplicity and the explicit diagnostic hint.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the schema is trivially complete. Baseline for 0 params is 4, and the description adds no unnecessary parameter information since none exists. It does not need to compensate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific purpose: to confirm cookie validity and list the user's communities. It clearly identifies the tool as an auth check combined with a listing operation, and this distinguishes it from sibling tools like list_posts or list_courses.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly tells the agent to call this first if other tools error, framing it as a diagnostic for auth/cookie problems. This provides clear when-to-use guidance and effectively positions it against the other tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
Each tool addresses a distinct resource and action: posts, comments, members, courses, conversations, and messages. The read/write tools are clearly separated (list/get vs create/send), and the whoami diagnostic is unique. No two tools appear to overlap in purpose.
All tools follow a consistent skool_<verb>_<noun> pattern (e.g., skool_list_posts, skool_get_post, skool_send_message). Even the outlier skool_whoami is a common convention for auth checks. The naming is predictable and groups resources and actions logically.
13 tools is well within the ideal 3–15 range and matches the server's breadth: community posts, comments, member directory, course content, and DM messaging. Each tool serves a clear purpose with no redundancy. The count feels appropriately scoped for a community platform.
Core workflows are covered: reading/writing posts, commenting, listing/reading conversations, sending DMs, and browsing course lessons. Minor gaps exist—there is no tool to update or delete posts/comments, and no search across posts or courses—but these are not critical for typical usage and may reflect API limitations.
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