Strava MCP Server
Strava MCP 服务器
该项目用 TypeScript 实现了一个模型上下文协议 (MCP) 服务器,作为连接 Strava API 的桥梁。它将 Strava 的数据和功能公开为大型语言模型 (LLM) 可以通过 MCP 标准利用的“工具”。
特征
🏃 访问最近的活动、个人资料和统计数据。
📊 获取详细的活动流(功率、心率、节奏等)。
🗺️ 探索、查看、加星标和管理片段。
⏱️查看详细的活动和细分工作量信息。
📍 列出并查看已保存路线的详细信息。
💾 将 GPX 或 TCX 格式的路线导出到本地文件系统。
🤖 通过 MCP 实现 AI 友好的 JSON 响应。
🔧 使用 Strava API V3。
Related MCP server: Strava MCP Server
自然语言交互示例
向你的 AI 助手询问如下问题,以便与你的 Strava 数据进行交互:
近期活动和个人资料:
“显示我最近的 Strava 活动。”
“我最近三次骑行经历是怎样的?”
“获取我的 Strava 个人资料信息。”
“我的 Strava 用户名是什么?”
活动流和数据:
“获取我昨天晨跑的心率数据。”
“显示我上次骑行的功率数据。”
“我周末百公里骑行的节奏是多少?”
“获取我周四晚上锻炼的所有流数据。”
“向我展示攀登魔鬼山的海拔剖面图。”
统计数据:
“我今年在 Strava 上的跑步统计数据是什么?”
“我一共骑了多远?”
“显示我的所有游泳记录。”
具体活动:
“告诉我上次跑步的详细信息。”
“我周二的间歇训练的平均功率是多少?”
“我昨天骑 Trek 自行车上下班了吗?”
俱乐部:
“我加入了哪些 Strava 俱乐部?”
“列出我加入的俱乐部。”
段:
“列出我在科罗拉多州博尔德附近主演的片段。”
“显示我最喜欢的片段。”
“获取‘Alpe du Zwift’ 路段的详细信息。”
“金门公园附近有没有什么好的跑步路段?”
“寻找博尔德斯弗拉格斯塔夫山附近的具有挑战性的攀登路线。”
“为我加注‘攀登旗杆路’部分。”
“取消‘左手峡谷’片段的星标。”
细分领域努力:
“本月在‘阳光峡谷’环节展现我的努力。”
“列出我今年 1 月至 6 月在 Box Hill 的尝试。”
“获取我在阿尔卑斯山的私人记录的详细信息。”
路线:
“列出我保存的 Strava 路线。”
“显示我的路线的第二页。”
“我的博尔德环线路线的海拔高度是多少?”
“获取我的‘Boulder Loop’路线的描述。”
“将我的‘Boulder Loop’路线导出为 GPX 文件。”
“将我周日早上的路线保存为 TCX 文件。”
高级提示示例
以下是更高级提示的示例,用于创建专业自行车教练对您的 Strava 活动的分析:
You are Tom Verhaegen, elite cycling coach and mentor to world champion Mathieu van der Poel. Analyze my most recent Strava activity. Provide a thorough, data-driven assessment of the ride, combining both quantitative insights and textual interpretation.
Begin your report with a written summary that highlights key findings and context. Then, bring the raw numbers to life: build an interactive, visually striking dashboard using HTML, CSS, and JavaScript. Use bold, high-contrast colors and intuitive, insightful chart types that best suit each metric (e.g., heart rate, power, cadence, elevation).
Embed clear coaching feedback and personalized training recommendations directly within the visualization. These should be practical, actionable, and grounded solely in the data provided—no assumptions or fabrications.
As a bonus, sprinkle in motivational quotes and cheeky commentary from Mathieu van der Poel himself—he's been watching my rides with one eyebrow raised and a smirk of both concern and amusement.
Goal: Deliver a professional-grade performance analysis that looks and feels like it came straight from the inner circle of world-class cycling.此提示会对您最近的 Strava 活动进行个性化分析,并附上专业指导反馈和自定义可视化仪表板。
⚠️ 重要的设置顺序
为了成功与 Claude 集成,请按照以下步骤操作:
安装服务器及其依赖项
在 Claude 的配置中配置服务器
完成 Strava 身份验证流程
重新启动 Claude 以确保正确加载环境变量
跳过步骤或按顺序执行可能会导致 Claude 无法正确读取环境变量。
安装和设置
先决条件:
Node.js(建议使用 v18 或更高版本)
npm(通常随 Node.js 提供)
Strava 帐户
1. 从源头
克隆存储库:
git clone https://github.com/r-huijts/strava-mcp.git cd strava-mcp安装依赖项:
npm install构建项目:
npm run build
2.配置Claude桌面
更新您的 Claude 配置文件:
{
"mcpServers": {
"strava-mcp-local": {
"command": "node",
"args": [
"/absolute/path/to/your/strava-mcp/dist/server.js"
]
// Environment variables are read from the .env file by the server
}
}
}确保将/absolute/path/to/your/strava-mcp/替换为您安装的实际路径。
3. Strava 身份验证设置
setup-auth.ts脚本可让您轻松使用 Strava API 设置身份验证。请仔细遵循以下步骤:
创建 Strava API 应用程序
创建新应用程序:
输入您的应用程序详细信息(名称、网站、描述)
重要提示:将“授权回调域”设置为
localhost记下您的客户端 ID 和客户端密钥
运行安装脚本
# In your strava-mcp directory
npx tsx scripts/setup-auth.ts按照提示完成身份验证流程(详细说明见下面的身份验证部分)。
4.重启克劳德
完成以上所有步骤后,重新启动 Claude Desktop 以使更改生效。这可确保:
新配置已加载
环境变量已正确读取
Strava MCP 服务器已正确初始化
🔑 环境变量
多变的 | 描述 |
STRAVA_CLIENT_ID | 您的 Strava 应用程序客户端 ID(必填) |
STRAVA_CLIENT_SECRET | 您的 Strava 应用程序客户端密钥(必需) |
STRAVA_ACCESS_TOKEN | 您的 Strava API 访问令牌(在设置过程中生成) |
STRAVA_REFRESH_TOKEN | 您的 Strava API 刷新令牌(在设置过程中生成) |
路由导出路径 | 保存导出的路线文件的绝对路径(可选) |
令牌处理
本服务器实现了令牌自动刷新功能。当初始访问令牌过期(通常为 6 小时后)时,服务器将自动使用.env中存储的刷新令牌获取新的访问令牌和刷新令牌。新的令牌会在运行的进程和.env文件中同步更新,从而确保服务器持续运行。
您只需运行一次scripts/setup-auth.ts脚本即可进行初始设置。
配置导出路径(可选)
如果您打算使用export-route-gpx或export-route-tcx工具,则需要指定一个用于保存导出文件的目录。
编辑您的.env文件并添加/更新ROUTE_EXPORT_PATH变量:
# Optional: Define an *absolute* path for saving exported route files (GPX/TCX)
# Ensure this directory exists and the server process has write permissions.
# Example: ROUTE_EXPORT_PATH=/Users/your_username/strava-exports
ROUTE_EXPORT_PATH=将占位符替换为所需导出目录的绝对路径。确保该目录存在并且服务器具有写入权限。
API 参考
该服务器公开以下 MCP 工具:
get-recent-activities
获取经过身份验证的用户的最近活动。
**使用时间:**当用户询问他们最近的锻炼、活动、跑步、骑行等情况时。
参数:
perPage(可选):类型:
number描述:要检索的活动数量。
默认值:30
**输出:**最近活动的格式化文本列表(姓名、ID、距离、日期)。
**错误:**丢失/无效的令牌,Strava API 错误。
get-athlete-profile
获取已验证运动员的个人资料信息。
**何时使用:**当用户询问其个人资料详细信息、用户名、位置、体重、高级状态等时。
**参数:**无
**输出:**带有配置文件详细信息的格式化文本字符串。
**错误:**丢失/无效的令牌,Strava API 错误。
get-athlete-stats
获取已认证运动员的活动统计数据(最近、年初至今、所有时间)。
**何时使用:**当用户询问他们的总体统计数据、跑步/骑行/游泳的总数、个人记录(最长骑行、最大爬升)时。
**参数:**无
**输出:**格式化的统计数据文本摘要,尊重用户的测量偏好。
**错误:**丢失/无效的令牌,Strava API 错误。
get-activity-details
使用特定活动的 ID 获取有关该活动的详细信息。
**何时使用:**当用户询问有关由其 ID 标识的特定活动的详细信息时。
参数:
activityId(必填):类型:
number描述:活动的唯一标识符。
**输出:**格式化的文本字符串,包含详细的活动信息(类型、日期、距离、时间、速度、心率、功率、装备等),尊重用户的测量偏好。
**错误:**丢失/无效的令牌、无效的
activityId、Strava API 错误。
list-athlete-clubs
列出已认证运动员所属的俱乐部。
**使用时机:**当用户询问自己加入的俱乐部时。
**参数:**无
**输出:**俱乐部的格式化文本列表(名称、ID、运动、会员、位置)。
**错误:**丢失/无效的令牌,Strava API 错误。
list-starred-segments
列出已认证运动员出演的片段。
**何时使用:**当用户询问他们加星标或喜欢的片段时。
**参数:**无
**输出:**带星号的片段的格式化文本列表(名称、ID、类型、距离、等级、位置)。
**错误:**丢失/无效的令牌,Strava API 错误。
get-segment
使用 ID 获取有关特定段的详细信息。
**何时使用:**当用户询问有关由其 ID 标识的特定段的详细信息时。
参数:
segmentId(必填):类型:
number描述:段的唯一标识符。
**输出:**格式化的文本字符串,包含详细的段信息(距离、等级、海拔、位置、星级、努力程度等),尊重用户的测量偏好。
**错误:**丢失/无效的令牌、无效的
segmentId、Strava API 错误。
explore-segments
在给定的地理区域(边界框)内搜索热门片段。
**何时使用:**当用户想要查找或发现特定地理区域内的路段时,可选择按活动类型或攀登类别进行筛选。
参数:
bounds(必需):类型:
string描述:以逗号分隔:
south_west_lat,south_west_lng,north_east_lat,north_east_lng。
activityType(可选):类型:
string("running"或"riding")描述:按活动类型过滤。
minCat(可选):类型:
number(0-5)描述:最低爬坡等级。要求
activityType: 'riding'。
maxCat(可选):类型:
number(0-5)描述:最大爬坡等级。需要
activityType: 'riding'。
**输出:**找到的段的格式化文本列表(名称、ID、爬升类别、距离、等级、海拔)。
**错误:**缺失/无效的令牌、无效的
bounds格式、无效的过滤器组合、Strava API 错误。
star-segment
为已认证运动员的特定片段添加或取消星标。
**何时使用:**当用户明确要求为通过其 ID 标识的特定片段加星标、收藏、取消星标或取消收藏时。
参数:
segmentId(必填):类型:
number描述:段的唯一标识符。
starred(必填):类型:
boolean描述:
true则为星号,false则为取消星号。
**输出:**确认操作和片段的新加星状态的成功消息。
**错误:**丢失/无效的令牌、无效的
segmentId、Strava API 错误(例如,未找到段、速率限制)。
get-segment-effort
使用 ID 获取有关特定细分工作的详细信息。
**何时使用:**当用户询问有关由其 ID 标识的特定细分工作的详细信息时。
参数:
effortId(必填):类型:
number描述:分段工作的唯一标识符。
**输出:**带有详细工作量信息(段名称、活动 ID、时间、距离、HR、功率、排名等)的格式化文本字符串。
**错误:**丢失/无效的令牌、无效的
effortId、Strava API 错误。
list-segment-efforts
列出经过验证的运动员在特定赛段上的努力,可选择按日期进行过滤。
**何时使用:**当用户要求列出他们在特定细分市场(可能在某个日期范围内)的努力或尝试时。
参数:
segmentId(必填):类型:
number描述:段的 ID。
startDateLocal(可选):类型:
string(ISO 8601 格式)描述:过滤在此日期时间之后开始的工作。
endDateLocal(可选):类型:
string(ISO 8601 格式)描述:过滤在此日期时间之前结束的工作。
perPage(可选):类型:
number描述:每页的结果数。
默认值:30
**输出:**匹配的细分工作的格式化文本列表。
**错误:**丢失/无效的令牌、无效的
segmentId、无效的日期格式、Strava API 错误。
list-athlete-routes
列出经过验证的运动员创建的路线。
**何时使用:**当用户要求查看他们创建或保存的路线时。
参数:
page(可选):类型:
number描述:分页的页码。
perPage(可选):类型:
number描述:每页的路线数。
默认值:30
**输出:**路线的格式化文本列表(名称、ID、类型、距离、海拔、日期)。
**错误:**丢失/无效令牌,Strava API 错误。
get-route
使用特定路线的 ID 获取其详细信息。
**何时使用:**当用户询问有关由其 ID 标识的特定路线的详细信息时。
参数:
routeId(必填):类型:
number描述:路线的唯一标识符。
**输出:**带有路线详细信息(名称、ID、类型、距离、海拔、预计时间、描述、路段数)的格式化文本字符串。
**错误:**丢失/无效的令牌、无效的
routeId、Strava API 错误。
export-route-gpx
以 GPX 格式导出特定路线并将其保存在本地。
**何时使用:**当用户明确要求将特定路线导出或保存为 GPX 文件时。
**前提条件:**服务器上必须正确配置
ROUTE_EXPORT_PATH环境变量。参数:
routeId(必填):类型:
number描述:路线的唯一标识符。
**输出:**指示保存位置的成功消息,或错误消息。
**错误:**丢失/无效的令牌、丢失/无效的
ROUTE_EXPORT_PATH、文件系统错误(权限、磁盘空间)、无效的routeId、Strava API 错误。
export-route-tcx
将特定路线以 TCX 格式导出并保存在本地。
**何时使用:**当用户明确要求将特定路线导出或保存为 TCX 文件时。
**前提条件:**服务器上必须正确配置
ROUTE_EXPORT_PATH环境变量。参数:
routeId(必填):类型:
number描述:路线的唯一标识符。
**输出:**指示保存位置的成功消息,或错误消息。
**错误:**丢失/无效的令牌、丢失/无效的
ROUTE_EXPORT_PATH、文件系统错误(权限、磁盘空间)、无效的routeId、Strava API 错误。
get-activity-streams
从 Strava 活动中检索详细的时间序列数据流,非常适合分析锻炼指标、可视化路线或执行详细的活动分析。
**何时使用:**当您需要某项活动的详细时间序列数据时:
通过心率区分析锻炼强度
计算骑行活动的功率指标
使用 GPS 坐标可视化路线数据
分析步速和海拔变化
详细细分分析
参数:
id(必填):类型:
number | string描述:用于获取流的 Strava 活动标识符
types(可选):类型:
array默认值:
['time', 'distance', 'heartrate', 'cadence', 'watts']可用类型:
time:从开始算起的时间(秒)distance:距起点的距离(以米为单位)latlng:[纬度,经度] 对的数组altitude:海拔(米)velocity_smooth:平滑速度(米/秒)heartrate:心率(每分钟心跳数)cadence:每分钟转数watts:输出功率(瓦特)temp:摄氏度moving:布尔值,指示是否移动grade_smooth:道路等级百分比
resolution(可选):类型:
string值:
'low'(~100 分)、'medium'(~1000 分)、'high'(~10000 分)描述:数据分辨率/密度
series_type(可选):类型:
string值:
'time'或'distance'默认值:
'distance'描述:数据点索引的基本系列类型
page(可选):类型:
number默认值:1
描述:分页结果的页码
points_per_page(可选):类型:
number默认值:100
特殊值:
-1返回拆分成多条消息的所有数据点描述:每页数据点的数量
输出格式:
元数据:
可用的流类型
总数据点
分辨率和系列类型
分页信息(当前页,总页数)
统计数据(如适用):
心率:最大、最小、平均
功率:最大、平均、标准化功率
速度:最大速度和平均速度(公里/小时)
流数据:
每个请求流的格式化时间序列数据
人类可读的格式(例如格式化的时间、速度的 km/h)
一致的数值精度
标记数据点
示例请求:
{ "id": 12345678, "types": ["time", "heartrate", "watts", "velocity_smooth", "cadence"], "resolution": "high", "points_per_page": 100, "page": 1 }特殊功能:
大型数据集的智能分页
完整数据检索模式(points_per_page = -1)
丰富的统计数据和元数据
格式化输出,供人类和 LLM 使用
自动单位转换
笔记:
需要活动:阅读范围
并非所有活动都适用所有流
较旧的活动可能数据有限
大型活动会自动分页
流可用性取决于录制设备和活动类型
错误:
令牌缺失/无效
活动 ID 无效
权限不足
不可用的流类型
分页参数无效
get-activity-laps
检索特定 Strava 活动记录的圈数。
何时使用:
分析活动不同部分(圈)的表现变化。
比较单圈时间、速度、心率或功率输出。
了解活动的结构(例如间歇训练)。
参数:
id(必填):类型:
number | string描述:Strava 活动的唯一标识符。
**输出格式:**详细描述每一圈的文本摘要,包括:
圈数索引
圈数名称(如有)
已用时间(格式为 HH:MM:SS)
移动时间(格式为 HH:MM:SS)
距离(公里)
平均速度(公里/小时)
最大速度(公里/小时)
总海拔高度(米)
平均心率(如有,以 bpm 为单位)
最大心率(如有,以 bpm 为单位)
平均节奏(如有,以 rpm 为单位)
平均瓦数(如有,以瓦为单位)
示例请求:
{ "id": 1234567890 }响应片段示例:
Activity Laps Summary (ID: 1234567890): Lap 1: Warmup Lap Time: 15:02 (Moving: 14:35) Distance: 5.01 km Avg Speed: 20.82 km/h Max Speed: 35.50 km/h Elevation Gain: 50.2 m Avg HR: 135.5 bpm Max HR: 150 bpm Avg Cadence: 85.0 rpm Lap 2: Interval 1 Time: 05:15 (Moving: 05:10) Distance: 2.50 km Avg Speed: 29.03 km/h Max Speed: 42.10 km/h Elevation Gain: 10.1 m Avg HR: 168.2 bpm Max HR: 175 bpm Avg Cadence: 92.1 rpm Avg Power: 280.5 W (Sensor) ...笔记:
需要
activity:read公共/关注者活动的范围,activity:read_all私人活动的范围。圈数数据的可用性取决于记录设备和活动类型(例如,手动活动可能没有圈数)。
错误:
令牌缺失/无效
活动 ID 无效
权限不足
未找到活动
get-athlete-zones
检索经过验证的运动员配置的心率和功率区。
**何时使用:**当用户询问他们的心率区、功率区或训练区设置时。
**参数:**无
**输出格式:**返回两个文本块:
详细说明已配置区域的格式化摘要:
心率区:自定义状态、区域范围、时间分布(如果可用)
功率区:区域范围、时间分布(如果可用)
Strava API 返回的完整原始 JSON 数据。
响应片段示例(摘要):
**Athlete Zones:** ❤️ **Heart Rate Zones** Custom Zones: No Zone 1: 0 - 115 bpm Zone 2: 115 - 145 bpm Zone 3: 145 - 165 bpm Zone 4: 165 - 180 bpm Zone 5: 180+ bpm ⚡ **Power Zones** Zone 1: 0 - 150 W Zone 2: 151 - 210 W Zone 3: 211 - 250 W Zone 4: 251 - 300 W Zone 5: 301 - 350 W Zone 6: 351 - 420 W Zone 7: 421+ W Time Distribution: - 0-50: 0:24:58 - 50-100: 0:01:02 ... - 450-∞: 0:05:43笔记:
需要配置
profile:read_all范围。区域可能并未针对所有运动员进行配置。
错误:
令牌缺失/无效
权限不足(缺少
profile:read_all范围 - 403 错误)需要订阅(如果 Strava 更改 API 访问权限,则可能需要订阅)
贡献
欢迎贡献代码!欢迎提交 Pull 请求。
执照
本项目采用 MIT 许可证 - 详情请参阅 LICENSE 文件。(假设采用 MIT 许可证,如有不同,请更新)
Available Tools
24 toolscheck-strava-connectionA
Check if Strava is connected and show the current connection status. Use this when the user asks about their connection status.
| 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 burden of behavioral disclosure. The term 'check' and 'show' imply a non-mutating, read-only operation, which is sufficient for a simple status check. It does not explicitly state that no changes are made, but the nature of the action and the lack of parameters make this transparent enough.
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 long and front-loaded with the primary purpose. Every word earns its place, with no repetition or fluff, making it highly concise and well-structured.
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 is complete. It clearly states what the tool does and when to use it, and the sibling context shows how it fits into the connection management workflow. There is no missing information that would hinder an agent from invoking it 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?
The tool has zero parameters, so the baseline is 4. The empty input schema requires no additional explanation, and the description appropriately does not attempt to document parameters that do not exist.
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 checks and shows Strava connection status, using the specific verb 'check' and resource 'connection status'. This distinguishes it from sibling tools like connect-strava and disconnect-strava, which manage the connection, and data-fetching tools that retrieve stats.
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 says 'Use this when the user asks about their connection status,' providing clear guidance on when to invoke the tool. It does not explicitly mention when not to use it or compare to alternatives, but the context is strong enough for an agent to differentiate it from connect/disconnect tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
connect-stravaA
Connect your Strava account to enable activity tracking. This will open a browser window for secure authentication. Use this when the user asks to connect, link, or authenticate their Strava account.
| Name | Required | Description | Default |
|---|---|---|---|
| force | No | Force re-authentication even if already connected |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry full transparency burden. It discloses that authentication opens a browser window, which is helpful, but it does not explain what happens if the account is already connected, whether the 'force' option is necessary, or any side effects beyond the authentication flow. For a mutation-like action, this is a significant gap.
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 action and followed by the usage condition. Every word serves a purpose, with no filler or redundancy.
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 OAuth connect tool with one optional parameter and no output schema, the description covers the core action and when to use it. However, it omits details about what happens after connection, such as success/failure indication or behavior when already authenticated, which is useful context for an agent.
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 already fully documents the single 'force' parameter with a clear description ('Force re-authentication even if already connected'). The description adds no further parameter semantics, so the baseline score of 3 applies.
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: 'Connect your Strava account to enable activity tracking.' This specifies the verb and resource, and it naturally distinguishes from sibling tools like 'disconnect-strava' and 'check-strava-connection'.
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?
Explicit usage guidance is provided: 'Use this when the user asks to connect, link, or authenticate their Strava account.' This gives clear context for when to invoke the tool, though it does not discuss exclusions or alternatives, which is acceptable given the tool's distinct purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
disconnect-stravaA
Disconnect your Strava account and remove stored credentials. Use this when the user wants to logout, disconnect, or remove their Strava connection.
| 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 transparency burden. It explicitly discloses the key side effect: 'remove stored credentials.' This goes beyond the name and informs the agent of the security-relevant action. It doesn't detail irreversibility or effects on other services, but for a zero-parameter tool this is adequate and notably transparent.
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, each earning its place: the first states the action, the second states when to use it. Front-loaded and free of filler. Excellent structure.
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 action tool with no parameters and no output schema, the description is complete: it covers what, why, when, and the side effect. Sibling tools help disambiguate, and the description is self-sufficient. No gaps remain.
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 baseline is 4. The description adds no parameter-specific information because none is needed. It appropriately focuses on the action and usage context, which is all that matters here.
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 uses a specific verb ('Disconnect') and identifies the resource ('your Strava account') plus additional detail ('remove stored credentials'). It clearly distinguishes this tool from siblings like connect-strava and check-strava-connection, which serve different purposes.
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?
Provides explicit guidance: 'Use this when the user wants to logout, disconnect, or remove their Strava connection.' This clearly states the intended use case. However, it lacks explicit 'when not to use' or alternative tool references, so it falls slightly short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
explore-segmentsC
Searches for popular segments within a given geographical area.
| Name | Required | Description | Default |
|---|---|---|---|
| bounds | Yes | The geographical area to search, specified as a comma-separated string: south_west_lat,south_west_lng,north_east_lat,north_east_lng | |
| activityType | No | Filter segments by activity type (optional: 'running' or 'riding'). | |
| minCat | No | Filter by minimum climb category (optional, 0-5). Requires riding activityType. | |
| maxCat | No | Filter by maximum climb category (optional, 0-5). Requires riding activityType. |
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 mentions searching for 'popular segments' but doesn't specify what makes a segment 'popular' (e.g., based on usage, ratings, or other metrics), nor does it describe the return format, pagination, or any rate limits or authentication requirements. This leaves significant gaps in understanding the tool's behavior.
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, clear sentence that efficiently conveys the core functionality without unnecessary words. It is front-loaded with the main action and resource, making it easy to understand at a glance.
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 complexity of a search tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits (e.g., how popularity is determined, result format), usage context, and differentiation from siblings. This makes it inadequate for an AI agent to fully understand when and how to invoke the tool effectively.
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 description coverage is 100%, meaning all parameters are well-documented in the schema itself. The description adds no additional parameter semantics beyond implying a geographical search, which is already covered by the 'bounds' parameter description. Thus, it meets the baseline score of 3 without adding extra 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 the tool's purpose with a specific verb ('searches') and resource ('popular segments'), and specifies the geographical scope. However, it doesn't differentiate from sibling tools like 'list-starred-segments' or 'get-segment', which might also retrieve segments but with different criteria or scope.
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 no guidance on when to use this tool versus alternatives like 'list-starred-segments' or 'get-segment', nor does it mention prerequisites such as requiring a connected Strava account. It only states what the tool does without contextual usage advice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export-route-gpxA
Exports a specific Strava route in GPX format and saves it to a pre-configured local directory.
| Name | Required | Description | Default |
|---|---|---|---|
| routeId | Yes | The ID of the Strava route to export. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It does disclose a key side effect: 'saves it to a pre-configured local directory,' which is important for an agent to know. However, it does not mention authentication requirements, error handling, file naming, or whether the operation overwrites existing files. This is adequate but not rich behavioral 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?
The description is a single sentence that is concise, front-loaded with the action, and contains no redundant information. Every phrase earns its place: specifies the export format, the resource, and the destination.
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 one required parameter and no output schema, the description covers the essential context: what it exports, in what format, and where it saves. It lacks information about return values (e.g., success message) and potential failure modes, but given the simple nature of the tool and the rich schema, the description is sufficiently complete. A score of 4 reflects that it could add a note about output or prerequisites but is otherwise adequate.
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 input schema covers 100% of parameter semantics: routeId is described as 'The ID of the Strava route to export.' The description adds no additional parameter-level detail beyond the schema, but it reinforces the meaning by referring to 'a specific Strava route.' Per calibration, with schema coverage at 100%, a baseline score of 3 is appropriate.
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 function: 'Exports a specific Strava route in GPX format and saves it to a pre-configured local directory.' It specifies the verb (exports), resource (specific Strava route), output format (GPX), and side effect (saving to a local directory). This distinguishes it from sibling tools like export-route-tcx (different format) and get-route (retrieval without file output).
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 when to use this tool (when a GPX export of a route is needed) but does not explicitly provide usage exclusions or name alternatives. Since sibling tools exist (e.g., export-route-tcx for TCX format), the description could have stated 'use this for GPX, export-route-tcx for TCX' to improve guidance. The context is clear but lacks explicit alternative comparison.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
export-route-tcxA
Exports a specific Strava route in TCX format and saves it to a pre-configured local directory.
| Name | Required | Description | Default |
|---|---|---|---|
| routeId | Yes | The ID of the Strava route to export. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses a key behavioral trait—saving to a pre-configured local directory—which implies a mutating side effect. However, it omits other useful behavioral context such as overwrite behavior, authentication requirements, or error conditions.
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 that conveys the core purpose, format, and destination with no redundancy or unnecessary detail.
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 one-parameter tool, the description covers the essential elements: what is exported, the format, and the destination. It lacks minor details like return value or prerequisites, but given the absence of annotations and output schema, it is reasonably 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?
The schema already provides 100% coverage for the single parameter routeId with a clear description. The tool description adds no additional meaning beyond what the schema states, so the baseline score of 3 is appropriate.
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 ('Exports... in TCX format'), the specific resource ('a specific Strava route'), and a unique side effect ('saves it to a pre-configured local directory'). It distinguishes the tool from the sibling export-route-gpx by format (TCX vs GPX).
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 usage for exporting a route in TCX format, but it does not explicitly mention when to use this over export-route-gpx or other route tools. No exclusions or alternative comparisons are provided, leaving usage guidance only implicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-activity-detailsC
Fetches detailed information about a specific activity using its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| activityId | Yes | The unique identifier of the activity to fetch details for. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states it 'fetches detailed information' without disclosing behavioral traits. It doesn't mention whether this is a read-only operation, what permissions are needed, rate limits, error conditions, or what format/details are returned. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.
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 that gets straight to the point with zero wasted words. It's appropriately sized for a simple lookup tool and front-loads the core functionality without unnecessary elaboration.
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 lack of annotations and output schema, the description is insufficiently complete. It doesn't explain what 'detailed information' includes, the response format, or any behavioral aspects. For a tool in a complex domain (Strava activities) with many sibling tools, more context is needed to understand its specific role and output.
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 description coverage is 100% with the single parameter 'activityId' well-documented in the schema. The description adds no additional parameter semantics beyond implying the ID is used to fetch details. Since the schema does the heavy lifting, the baseline score of 3 is appropriate even though the description doesn't enhance parameter understanding.
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 verb 'fetches' and resource 'detailed information about a specific activity', making the purpose understandable. It distinguishes from siblings like 'get-all-activities' by specifying 'specific activity using its ID', but doesn't explicitly contrast with similar tools like 'get-activity-laps' or 'get-activity-streams' that also fetch activity-related data.
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 no guidance on when to use this tool versus alternatives. It doesn't mention when this tool is appropriate compared to siblings like 'get-all-activities' for listing activities or 'get-activity-streams' for different types of activity data. There's no context about prerequisites, timing, or exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-activity-lapsA
Retrieves detailed lap data for a specific Strava activity.
Use Cases:
Get complete lap data including timestamps, speeds, and metrics
Access raw values for detailed analysis or visualization
Extract specific lap metrics for comparison or tracking
Parameters:
id (required): The unique identifier of the Strava activity.
Output Format: Returns both a human-readable summary and complete JSON data for each lap, including:
A text summary with formatted metrics
Raw lap data containing all fields from the Strava API:
Unique lap ID and indices
Timestamps (start_date, start_date_local)
Distance and timing metrics
Speed metrics (average and max)
Performance metrics (heart rate, cadence, power if available)
Elevation data
Resource state information
Activity and athlete references
Notes:
Requires activity:read scope for public/followers activities, activity:read_all for private activities
Returns complete data as received from Strava API without omissions
All numeric values are preserved in their original precision
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The identifier of the activity to fetch laps for. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and does well by disclosing important behavioral traits: authentication requirements ('Requires activity:read scope...'), data completeness ('Returns complete data... without omissions'), and precision handling ('All numeric values are preserved...'). It doesn't mention rate limits or error conditions, keeping it from a perfect score.
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?
Excellent structure with clear sections (Description, Use Cases, Parameters, Output Format, Notes). Every sentence earns its place by adding specific value - no redundant information. The description is appropriately sized and front-loaded with the core purpose.
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 read operation with no output schema, the description provides exceptional completeness. It covers authentication requirements, data scope, output format details (both human-readable and JSON), and specific data fields returned. This gives the agent sufficient context to use the tool effectively.
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 100%, so the schema already documents the single 'id' parameter adequately. The description adds minimal value beyond the schema by specifying it's for 'a specific Strava activity' and listing it in the Parameters section, but doesn't provide additional syntax or format details.
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 purpose with specific verb ('Retrieves') and resource ('detailed lap data for a specific Strava activity'). It distinguishes from siblings like 'get-activity-details' by focusing exclusively on lap data rather than general activity information.
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 'Use Cases' section provides clear context for when to use this tool (detailed lap analysis, visualization, comparison). However, it doesn't explicitly state when NOT to use it or name specific alternatives among sibling tools, though the focus on lap data implies differentiation from general activity tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-activity-photosA
Retrieves photos associated with a specific Strava activity.
Use Cases:
Fetch all photos uploaded to an activity
Get photo URLs for display or download
Access photo metadata including location and timestamps
Parameters:
id (required): The unique identifier of the Strava activity.
size (optional): Size of photos to return in pixels (e.g., 100, 600, 2048). If not specified, returns all available sizes.
Output Format: Returns both a human-readable summary and complete JSON data for each photo, including:
A text summary with photo count and URLs
Raw photo data containing all fields from the Strava API:
Photo ID and unique identifier
URLs for different sizes
Source (1 = Strava, 2 = Instagram)
Timestamps (uploaded_at, created_at)
Location coordinates if available
Caption if provided
Notes:
Requires activity:read scope for public/followers activities, activity:read_all for private activities
Photos may come from Strava uploads or linked Instagram posts
Returns empty array if activity has no photos
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The identifier of the activity to fetch photos for. | |
| size | No | Optional photo size in pixels (e.g., 100, 600, 2048). |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Despite no annotations, the description discloses scope requirements (activity:read vs activity:read_all), the possibility of Instagram-sourced photos, and the empty-array behavior. It also explains the size parameter's default behavior, providing thorough transparency.
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 well-structured with clear sections. It could be slightly tighter in the output-format section, but every part serves a purpose and is easy to scan.
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 two-parameter tool with no annotations and no output schema, the description is exceptionally complete. It covers purpose, parameters, output structure, auth scopes, and edge cases, leaving no critical gaps.
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 already covers both parameters, but the description adds value with size examples and the behavior when size is omitted (returns all sizes). This enhances understanding beyond the schema's bare definition.
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 opens with a specific verb and resource: 'Retrieves photos associated with a specific Strava activity.' This clearly distinguishes it from sibling tools like get-activity-details or get-activity-streams, which handle other types of activity data.
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?
Use cases explicitly state when to use the tool: fetching photos, getting URLs, and accessing metadata. While it doesn't name alternative tools, the context makes the appropriate scenario clear. A slight improvement would be explicitly contrasting with other activity-data tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-activity-streamsA
Retrieves detailed time-series data streams from a Strava activity. Perfect for analyzing workout metrics, visualizing routes, or performing detailed activity analysis.
Key Features:
Multiple Data Types: Access various metrics like heart rate, power, speed, GPS coordinates, etc.
Flexible Resolution: Choose data density from low (~100 points) to high (~10000 points)
Smart Pagination: Get data in manageable chunks optimized for LLM context limits
Rich Statistics: Includes min/max/avg for numeric streams
Dual Format Support: Compact (LLM-optimized) or verbose (human-readable)
Intelligent Downsampling: Automatically reduce large datasets while preserving key features
Format Options:
compact (default): Raw arrays, minified JSON, ~70-80% smaller payloads, ideal for LLM processing
verbose: Human-readable objects with formatted values, backward compatible with legacy format
Common Use Cases:
Analyzing workout intensity through heart rate zones
Calculating power metrics for cycling activities
Visualizing route data using GPS coordinates
Analyzing pace and elevation changes
Detailed segment analysis
Output Format:
Metadata: Activity overview, available streams, data points, units, format info
Statistics: Summary stats for each stream type (max/min/avg where applicable)
Data: Time-series data in compact arrays or verbose objects (based on format parameter)
Notes:
Requires activity:read scope
Not all streams are available for all activities
Older activities might have limited data
Large activities are automatically chunked to ~50KB per message
Use max_points parameter to downsample very large activities intelligently
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | The Strava activity identifier to fetch streams for. This can be obtained from activity URLs or the get-activities tool. | |
| types | No | Array of stream types to fetch. Available types: - time: Time in seconds from start - distance: Distance in meters from start - latlng: Array of [latitude, longitude] pairs - altitude: Elevation in meters - velocity_smooth: Smoothed speed in meters/second - heartrate: Heart rate in beats per minute - cadence: Cadence in revolutions per minute - watts: Power output in watts - temp: Temperature in Celsius - moving: Boolean indicating if moving - grade_smooth: Road grade as percentage | |
| resolution | No | Optional data resolution. Affects number of data points returned: - low: ~100 points - medium: ~1000 points - high: ~10000 points Default varies based on activity length. | |
| series_type | No | Optional base series type for the streams: - time: Data points are indexed by time (seconds from start) - distance: Data points are indexed by distance (meters from start) Useful for comparing different activities or analyzing specific segments. | distance |
| page | No | Optional page number for paginated results. Use with points_per_page to retrieve specific data ranges. Example: page=2 with points_per_page=100 gets points 101-200. | |
| points_per_page | No | Optional number of data points per page. Special values: - Positive number: Returns that many points per page - -1: Returns ALL data points split into multiple messages (~1000 points each) Use -1 when you need the complete activity data for analysis. | |
| format | No | Output format: - compact: Raw arrays, minified JSON (~70-80% smaller, LLM-friendly) - verbose: Human-readable objects with formatted values (backward compatible) | compact |
| max_points | No | Maximum number of data points to return. If activity exceeds this, data will be intelligently downsampled while preserving peaks and valleys. Useful for very large activities. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden and excels by disclosing key behavioral traits: it requires 'activity:read scope', notes 'not all streams are available for all activities', warns 'older activities might have limited data', explains 'large activities are automatically chunked to ~50KB per message', and describes intelligent downsampling for large datasets. This covers permissions, data availability, limitations, and performance considerations thoroughly.
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 well-structured with sections like 'Key Features', 'Format Options', 'Common Use Cases', 'Output Format', and 'Notes', making it easy to scan. However, it is lengthy with multiple bullet points and detailed explanations, which, while informative, could be more concise. Every sentence adds value, but some redundancy exists (e.g., repeating format details).
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 complexity of 8 parameters, no annotations, and no output schema, the description is highly complete. It covers purpose, usage, behavioral traits, parameter semantics, output format details, and limitations. The 'Output Format' section compensates for the lack of output schema by describing metadata, statistics, and data structure, making it sufficient for an agent to understand what to expect.
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 description coverage is 100%, so the baseline is 3. The description adds significant value by explaining parameter implications beyond the schema: it details how 'resolution' affects data points (~100 to ~10000), describes 'smart pagination' for 'page' and 'points_per_page', explains 'intelligent downsampling' for 'max_points', and elaborates on 'format' options (compact vs verbose) with payload size impacts. This enhances understanding but doesn't fully cover all 8 parameters in depth.
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 'retrieves detailed time-series data streams from a Strava activity' with specific verbs ('retrieves', 'analyzing', 'visualizing') and resources ('Strava activity', 'workout metrics', 'routes'). It distinguishes from siblings like get-activity-details (which likely provides summary info) and get-activity-laps (which focuses on lap segments) by emphasizing time-series data streams for analysis.
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 states when to use this tool: 'Perfect for analyzing workout metrics, visualizing routes, or performing detailed activity analysis' and lists common use cases like analyzing heart rate zones, calculating power metrics, and visualizing GPS coordinates. It distinguishes from siblings by focusing on time-series data streams rather than summary details, photos, or segments.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-all-activitiesA
Fetches complete activity history with optional filtering by date range and activity type. Supports pagination to retrieve all activities.
| Name | Required | Description | Default |
|---|---|---|---|
| startDate | No | ISO date string for activities after this date (e.g., '2024-01-01') | |
| endDate | No | ISO date string for activities before this date (e.g., '2024-12-31') | |
| activityTypes | No | Array of activity types to filter (e.g., ['Run', 'Ride']) | |
| sportTypes | No | Array of sport types for granular filtering (e.g., ['MountainBikeRide', 'TrailRun']) | |
| maxActivities | No | Maximum activities to return after filtering (default: 500) | |
| maxApiCalls | No | Maximum API calls to prevent quota exhaustion (default: 10 = ~2000 activities) | |
| perPage | No | Activities per API call (default: 200, max: 200) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses pagination support and filtering capabilities, which is helpful. However, it doesn't mention authentication requirements, rate limits, error conditions, or what 'complete activity history' entails (e.g., all-time vs. limited period). The behavioral context is partially covered but incomplete.
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 efficiently structured in two sentences: the first states core functionality, the second adds important behavioral detail about pagination. Every word earns its place with zero redundancy or fluff.
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 7-parameter tool with no annotations and no output schema, the description provides basic functional context but lacks details about authentication, error handling, return format, or performance characteristics. It's minimally adequate given the schema handles parameter documentation, but more behavioral context would be helpful.
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 100%, so the schema fully documents all 7 parameters. The description adds minimal value beyond the schema by mentioning 'optional filtering by date range and activity type' and 'pagination', but doesn't provide additional semantic context about parameter interactions or usage patterns.
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 'fetches complete activity history' with filtering capabilities, providing a specific verb ('fetches') and resource ('activity history'). It distinguishes from sibling tools like 'get-recent-activities' by emphasizing 'complete' history, though it doesn't explicitly name alternatives.
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 usage for retrieving comprehensive activity data with filtering, but doesn't explicitly state when to use this versus alternatives like 'get-recent-activities' or 'get-activity-details'. No guidance on prerequisites, exclusions, or specific scenarios is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-athlete-profileA
Fetches the profile information for the authenticated athlete, including their unique numeric ID needed for other tools like get-athlete-stats.
| 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 burden of behavioral disclosure. It correctly uses 'Fetches' to imply a read-only operation and notes that it returns an ID, but it does not disclose details such as authentication scope, rate limits, or the exact set of profile fields returned. This is adequate for a simple no-parameter read tool but falls short of rich transparency.
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 sentence that is front-loaded with the action and resource, immediately states the output's key value, and includes a concrete example of downstream usage. Every word contributes, with no redundancy or filler.
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 read-only tool with no parameters and no output schema, the description is reasonably complete: it names the resource, identifies the primary output (numeric ID), and provides a usage link to other tools. However, it does not enumerate the full profile fields or specify any error conditions, so it stops short of a 5.
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 input schema is empty and no parameter documentation is required. The description adds meaningful context about the output (the numeric ID), which is more than the schema provides. Baseline for zero-parameter tools is 4, and this description meets that bar.
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 function with a specific verb ('Fetches') and resource ('profile information for the authenticated athlete'). It also explicitly distinguishes the tool by highlighting the unique numeric ID that other tools (e.g., get-athlete-stats) depend on, which sets it apart from sibling 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 provides clear usage context by stating the profile ID is needed for other tools like get-athlete-stats, implying this should be called first to obtain that ID. It does not explicitly mention when not to use it or list alternatives, but the guidance is practical and unambiguous for its intended role.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-athlete-statsA
Fetches the activity statistics (recent, YTD, all-time) for a specific athlete using their ID. Requires the athleteId obtained from the get-athlete-profile tool.
| Name | Required | Description | Default |
|---|---|---|---|
| athleteId | Yes | The unique identifier of the athlete to fetch stats for. Obtain this ID first by calling the get-athlete-profile tool. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions the prerequisite (athleteId requirement) which is useful context, but doesn't disclose other behavioral traits like rate limits, authentication needs, error conditions, or what the output format looks like (since no output schema exists).
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 zero waste. The first sentence states purpose and scope, the second provides critical prerequisite information. Every word earns its place and the description is appropriately sized for a single-parameter 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 read-only tool with 100% schema coverage but no annotations and no output schema, the description provides adequate purpose and usage guidance. However, it lacks information about return values (what the stats actually contain) and other behavioral context that would be helpful given the absence of structured output documentation.
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 100%, so the schema already documents the single parameter. The description adds value by explaining where to obtain the athleteId ('from the get-athlete-profile tool'), which provides practical guidance beyond the schema's technical specification.
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 specific action ('fetches') and resource ('activity statistics for a specific athlete'), specifying the types of statistics (recent, YTD, all-time). It distinguishes from siblings like 'get-athlete-profile' by focusing on stats rather than profile data.
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 states when to use this tool ('for a specific athlete using their ID') and provides a prerequisite ('Requires the athleteId obtained from the get-athlete-profile tool'), clearly differentiating it from alternatives that don't require this ID or fetch different data types.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-athlete-zonesA
Retrieves the authenticated athlete's configured heart rate and power zones.
Output includes both a formatted summary and the raw JSON data.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Although no annotations exist, the description adds useful context by specifying that output includes both a formatted summary and raw JSON, and it implies authentication scope with 'authenticated athlete.' However, it does not explicitly confirm read-only semantics or discuss any caveats.
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 deliver purpose and output details with no irrelevant content. Front-loaded 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 parameterless read operation, the description covers what it does and what it returns. There is no output schema to elaborate, and the complexity is low, so this is sufficient.
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?
There are zero parameters, so the description does not need to explain any inputs. The baseline of 4 applies, and the description adds no param-specific details.
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 identifies the action (retrieves) and the resource (the athlete's configured heart rate and power zones). This distinguishes it from sibling tools like get-athlete-stats or get-athlete-profile, making its purpose 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?
No explicit guidance is provided for when to use this tool instead of alternatives. The usage is implied by the clear purpose, but there are no exclusions or comparisons with sibling tools.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-recent-activitiesA
Fetches the most recent activities for the authenticated athlete.
| Name | Required | Description | Default |
|---|---|---|---|
| perPage | No | Number of activities to retrieve (default: 30) |
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 indicates a read operation ('Fetches'), which implies non-destructive behavior, but it does not disclose pagination behavior, rate limits, or what 'most recent' means in terms of time range. The verb provides basic transparency but not rich details.
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 sentence with no filler or redundancy. It is front-loaded with the verb and resource, making it easy to parse and understand quickly.
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 with one optional parameter and no output schema, so the description is largely adequate. However, it does not clarify how this differs from the sibling tool get-all-activities, which could lead to incorrect selection. Additionally, no behavioral edge cases are mentioned, leaving some context missing.
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 input schema covers the sole parameter (perPage) with a description and default value, yielding 100% schema coverage. The tool description does not mention the parameter, but the schema already explains it, so the baseline of 3 applies.
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 uses a specific verb 'Fetches' and a clear resource: 'most recent activities' for the authenticated athlete. The scope ('most recent') helps distinguish it from siblings like get-all-activities and get-activity-details.
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?
No guidance is provided on when to use this tool versus alternatives such as get-all-activities or get-activity-details. The description simply states what it does without giving context on when it is the preferred choice.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-routeA
Fetches detailed information about a specific route using its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| routeId | Yes | The unique identifier of the route to fetch. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description must carry behavioral information. 'Fetches' implies read-only, but the description does not mention authentication needs, error handling, or the exact nature of 'detailed information'. It adds minimal value beyond the obvious.
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 written sentence that front-loads the verb and resource. Every word earns its place, with no fluff or redundancy.
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 single-parameter fetch, the description covers the core purpose. However, without an output schema, 'detailed information' is vague about what exactly is returned. It also omits prerequisites or failure scenarios, leaving some gaps for an agent.
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 input schema already provides a complete description of the only parameter (routeId) with pattern and explanation. The description's 'using its ID' simply restates the schema, adding no extra meaning. With 100% schema coverage, the baseline of 3 applies.
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 uses 'fetches' with a specific resource ('a specific route') and method ('using its ID'), clearly distinguishing it from listing, searching, or exporting sibling tools. It is specific and 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?
No guidance is provided on when to use this tool versus alternatives like find-nearby-routes or list-athlete-routes. There are no exclusions, alternatives, or context for choosing this tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-segmentC
Fetches detailed information about a specific segment using its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| segmentId | Yes | The unique identifier of the segment to fetch. |
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 of behavioral disclosure. It states it 'fetches detailed information' but doesn't specify what 'detailed' includes, whether it's a read-only operation, if it requires authentication, or any rate limits. This leaves significant gaps for an agent to understand the tool's behavior.
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 that directly states the tool's function without unnecessary words. It's appropriately sized and front-loaded, making it easy to parse quickly.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'detailed information' includes, potential error cases, or authentication requirements. For a tool in a context with many siblings and no structured output, more context is needed for effective 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?
Schema description coverage is 100%, with the parameter 'segmentId' fully documented in the schema. The description adds no additional semantic context beyond implying it's used to fetch a segment, which aligns with the schema. This meets the baseline for high schema 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?
The description clearly states the verb ('fetches') and resource ('detailed information about a specific segment'), making the purpose understandable. However, it doesn't distinguish this tool from similar siblings like 'get-segment-effort' or 'list-segment-efforts', which reduces its differentiation value.
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 no guidance on when to use this tool versus alternatives like 'get-segment-effort' or 'list-segment-efforts'. It mentions using a segment ID but doesn't specify prerequisites, such as needing an authenticated connection or when this is the appropriate fetch method.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-segment-effortC
Fetches detailed information about a specific segment effort using its ID.
| Name | Required | Description | Default |
|---|---|---|---|
| effortId | Yes | The unique identifier of the segment effort to fetch. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states it 'fetches' information, implying a read-only operation, but doesn't disclose behavioral traits such as authentication requirements, rate limits, error handling, or what 'detailed information' entails (e.g., fields returned, format). This leaves gaps for safe and effective use.
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 that front-loads the core purpose ('fetches detailed information') without unnecessary words. Every part earns its place, making it easy to parse quickly.
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 no annotations and no output schema, the description is incomplete. It doesn't explain what 'detailed information' includes (e.g., fields like time, distance, athlete details), which is critical for a tool with one parameter and no structured output documentation. This leaves significant gaps for an agent to understand the tool's behavior and results.
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 100%, with the parameter 'effortId' well-documented in the schema. The description adds minimal value beyond the schema by mentioning 'using its ID', which aligns with but doesn't expand on the schema's description. Baseline 3 is appropriate as the schema does the heavy lifting.
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 ('fetches detailed information') and resource ('about a specific segment effort using its ID'), which distinguishes it from siblings like 'list-segment-efforts' (plural listing) and 'get-segment' (segment vs. segment effort). However, it doesn't specify what 'detailed information' includes, leaving some 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?
No explicit guidance on when to use this tool versus alternatives is provided. It doesn't mention prerequisites (e.g., needing an effort ID from 'list-segment-efforts'), contrast with 'get-segment' (which fetches segment metadata), or specify use cases like retrieving performance data for analysis.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get-server-versionA
Returns the Strava MCP server version and related metadata.
| 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 burden of disclosing behavior. It says 'Returns,' implying a safe read operation, but does not explicitly state non-mutating behavior, authentication needs, or side effects. For a simple version check this is adequate yet not highly transparent.
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?
A single sentence with a clear verb and object, no filler. It is appropriately sized for a trivial utility 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?
Given zero parameters, no output schema, and a simple informational purpose, the description fully covers the necessary context. There is no missing information that would hinder correct invocation or interpretation.
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 input schema has zero parameters, so no parameter details are needed. The 0-parameter baseline of 4 applies, since there is nothing for the description to add beyond what the schema already conveys.
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 uses the specific verb 'Returns' and clearly identifies the resource (Strava MCP server version and related metadata). This distinguishes it from sibling tools that focus on athlete data, activities, and segments.
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 use when you need server version info, but it does not explicitly state when to use this tool vs alternatives, nor does it mention any exclusions. Given no sibling provides this function, the lack of contrast is minor, but the guidance is still not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-athlete-clubsA
Lists the clubs the authenticated athlete is a member of.
| 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 must carry the burden of behavioral disclosure. It conveys that the operation is a read (List) and scoped to the authenticated athlete, but it does not mention pagination, required OAuth scopes, rate limits, or response format. This is basic transparency but not comprehensive.
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?
A single sentence front-loaded with the verb 'Lists', followed by the resource and scope. No wasted words, clear and directly to the point.
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, read-only list tool without an output schema, the description provides the essential information: what is listed and for whom. It could mention pagination or return type, but the simplicity of the tool makes the description adequately 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?
The tool has zero parameters and an empty input schema, so baseline for parameter semantics is 4. The description adds no parameter detail because there are none to explain.
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 verb (Lists), the resource (clubs), and the scope (the authenticated athlete's memberships). It is specific and distinguishes itself from sibling tools since no other club-related tool exists.
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 does not explicitly state when to use this tool over alternatives or provide exclusions, but the usage is implied: it is the tool for retrieving the authenticated athlete's club memberships. No alternative club tool exists, so ambiguity is low, but explicit guidance is missing.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-athlete-routesA
Lists the routes created by the authenticated athlete, with pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| page | No | Page number for pagination | |
| perPage | No | Number of routes per page (max 50) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the read-only listing nature and pagination, but does not describe return format, ordering, or specific authentication needs beyond the phrase 'authenticated athlete'. This is acceptable for a low-risk list operation, but some behavioral details are missing.
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 one concise sentence, front-loaded with the core purpose and including the key pagination detail. No wasted words or redundancy.
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 two optional parameters and no output schema, the description provides sufficient context: it states what is listed, ownership, and pagination. It does not specify the response shape, but that is less critical for a standard list endpoint.
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 100%: both 'page' and 'perPage' have descriptions with defaults, ranges, and meanings. The tool description adds no additional parameter context beyond the schema, so the baseline 3 is appropriate.
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 verb 'lists' and the resource 'routes', with scope 'created by the authenticated athlete'. This distinguishes it from siblings like 'get-route' (likely a single route) and 'list-athlete-clubs' (a different resource), making the purpose unmistakable.
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 usage for retrieving the authenticated athlete's routes, and the pagination mention indicates how to handle large result sets. It does not explicitly name alternatives or exclusion conditions, but the context is clear enough for a simple listing tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-segment-effortsA
Lists the authenticated athlete's efforts on a specific segment, optionally filtering by date.
| Name | Required | Description | Default |
|---|---|---|---|
| segmentId | Yes | The ID of the segment for which to list efforts. | |
| startDateLocal | No | Filter efforts starting after this ISO 8601 date-time (optional). | |
| endDateLocal | No | Filter efforts ending before this ISO 8601 date-time (optional). | |
| perPage | No | Number of efforts to return per page (default: 30, max: 200). |
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 of behavioral disclosure. It mentions 'Lists' and 'filtering by date', but does not describe pagination behavior (implied by 'perPage' in schema but not explained), authentication requirements, rate limits, or what the output looks like. For a tool with no annotations, this leaves significant behavioral gaps.
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 that front-loads the core purpose ('Lists the authenticated athlete's efforts on a specific segment') and adds optional filtering information. Every word earns its place with zero waste, making it highly concise and well-structured.
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 4 parameters with 100% schema coverage but no annotations and no output schema, the description is adequate for a read-only list tool but incomplete. It covers the purpose and basic filtering, but lacks details on authentication, pagination behavior, error handling, or return format, which are important for a tool with no structured 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 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by implying date filtering, but does not provide additional semantics or usage context for parameters. Baseline 3 is appropriate when the schema does the heavy lifting.
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 specific action ('Lists'), the resource ('the authenticated athlete's efforts on a specific segment'), and includes optional filtering by date. It distinguishes this tool from siblings like 'get-segment-effort' (singular) and 'get-all-activities' (broader scope), making the purpose precise and differentiated.
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 usage for listing efforts on a segment with optional date filtering, but does not explicitly state when to use this tool versus alternatives like 'get-all-activities' or 'get-segment-effort'. It provides some context (filtering by date) but lacks guidance on exclusions or specific scenarios where this tool is preferred over siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list-starred-segmentsA
Lists the segments starred by the authenticated athlete.
| 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 full burden. It indicates a read-only listing operation ('Lists') and ties data to the authenticated athlete, but does not disclose details about pagination, response format, or authorization requirements beyond the phrase 'authenticated athlete'.
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?
One concise sentence with no extraneous words; front-loaded and easily scanned.
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, no-parameter listing tool, the description adequately conveys the tool's main purpose. However, since there is no output schema, a bit more detail about the return value (e.g., array of segment summaries) could enhance completeness, but it's not critical.
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 input schema has zero parameters and 100% coverage, so the baseline is 4. The description need not explain parameters, and it doesn't add conflicting information.
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 uses the specific verb 'Lists' and clearly identifies the resource ('segments') and scope ('starred by the authenticated athlete'), making its purpose unambiguous and distinct from sibling tools like 'get-segment' or 'explore-segments'.
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 usage for viewing the authenticated athlete's starred segments but provides no explicit guidance on when to use this tool over alternatives or any exclusion criteria. The intended use case is clear from context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
star-segmentA
Stars or unstars a specific segment for the authenticated athlete.
| Name | Required | Description | Default |
|---|---|---|---|
| segmentId | Yes | The unique identifier of the segment to star or unstar. | |
| starred | Yes | Set to true to star the segment, false to unstar it. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries full responsibility for behavioral disclosure. It reveals the mutation (star/unstar) but does not disclose potential side effects, idempotency, required auth scopes, or what happens if the segment is already starred/unstarred. The mention of 'authenticated athlete' hints at authorization but lacks 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?
The description is a single concise sentence: 'Stars or unstars a specific segment for the authenticated athlete.' It front-loads the action and contains no superfluous words, making it highly 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 2-parameter boolean action, the description covers the core purpose. However, since there is no output schema and no annotations, the agent receives no information about return values, errors, or behavioral nuances. It is minimally complete but leaves gaps around expected outcomes and edge cases.
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 100%, with both segmentId and starred having clear descriptions. The tool description adds no extra meaning beyond what the schema already provides, so the baseline of 3 is appropriate. The schema sufficiently explains each parameter's purpose.
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 action: 'Stars or unstars a specific segment'. It specifies the resource (a specific segment) and the actor (the authenticated athlete). This distinguishes it from siblings like list-starred-segments, which lists segments rather than modifying their star status.
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 implicitly conveys usage: use this to change the starred status of a segment. However, it does not explicitly mention alternatives or when not to use, such as using list-starred-segments to view stars or get-segment for details. No exclusions are stated, so it is minimally sufficient but lacks explicit guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
5 tool updates
v1.0.1- Added
check-strava-connection - Added
connect-strava - Added
disconnect-strava - Changed
get-activity-streams2 fields changed- added
Input schema / properties / formatAdded value: +{ + "default": "compact", + "description": "Output format:\n- compact: Raw arrays, minified JSON (~70-80% smaller, LLM-friendly)\n- verbose: Human-readable objects with formatted values (backward compatible)", + "enum": [ + "compact", + "verbose" + ], + "type": "string" +} - added
Input schema / properties / max_pointsAdded value: +{ + "description": "Maximum number of data points to return. If activity exceeds this, data will be intelligently downsampled while preserving peaks and valleys. Useful for very large activities.", + "type": "number" +}
- Added
get-server-version
6 tool updates
v1.0.0- Added
get-activity-photos - Added
get-all-activities - Changed
get-athlete-profile1 field changed- removed
Input schema / additionalPropertiesRemoved value: -false
- Changed
get-athlete-zones1 field changed- removed
Input schema / additionalPropertiesRemoved value: -false
- Changed
list-athlete-clubs1 field changed- removed
Input schema / additionalPropertiesRemoved value: -false
- Changed
list-starred-segments1 field changed- removed
Input schema / additionalPropertiesRemoved value: -false
18 tool updates
- First observed
explore-segments - First observed
export-route-gpx - First observed
export-route-tcx - First observed
get-activity-details - First observed
get-activity-laps - First observed
get-activity-streams - First observed
get-athlete-profile - First observed
get-athlete-stats - First observed
get-athlete-zones - First observed
get-recent-activities - First observed
get-route - First observed
get-segment - First observed
get-segment-effort - First observed
list-athlete-clubs - First observed
list-athlete-routes - First observed
list-segment-efforts - First observed
list-starred-segments - First observed
star-segment
TDQS
Scored across 24 tools
Most tools have distinct purposes targeting specific Strava resources like activities, segments, routes, or athlete data, with clear boundaries. However, some overlap exists between get-all-activities and get-recent-activities, which could cause confusion about which to use for general activity retrieval, though descriptions help differentiate them by scope.
Tool names follow a consistent verb-noun pattern with hyphens (e.g., get-activity-details, list-athlete-clubs), making them predictable and readable. Minor deviations include check-strava-connection and export-route-gpx, which slightly break the pattern but maintain overall coherence.
With 24 tools, the count is borderline high for a Strava integration, potentially overwhelming for agents. While it covers many aspects of the Strava API, some tools like get-server-version or check-strava-connection might be considered non-essential, contributing to a slightly bloated set.
The tool set provides comprehensive coverage of the Strava domain, including athlete management, activities, segments, routes, and data export. It supports full CRUD-like operations (e.g., connect/disconnect, star/unstar, get/list) and handles key workflows like activity analysis and segment tracking without obvious gaps.
Maintenance
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