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Agent Skill · 效率

daily-strava-roast(每日斯特拉瓦烤肉)

daily-strava-roast 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

daily-strava-roast 是效率类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为接触敏感数据;许可证为 MIT-0,第三方扫描已通过,按安装量在效率类的 21,003 个 Skill 里排第 9,371。

总安装 6,106周安装 257GitHub Stars 公开资料未说明下载 2,138核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
0.2.5

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:daily-strava-roast(每日斯特拉瓦烤肉)
来源仓库:https://github.com/ranasalalali/daily-strava-roast
安装命令:
openclaw skills install daily-strava-roast
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install daily-strava-roast

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

生成 Strava 锻炼活动的趣味点评,提供幽默回顾与激励反馈。适合健身爱好者、跑步社群或社交账号运营者增加互动乐趣。基于活动数据生成个性化调侃内容,增强用户粘性。需绑定 Strava 账户并授权读取运动记录,否则无法获取数据。建议适度使用,避免过度戏谑影响社区氛围。

daily-strava-roast 属于效率类 Skill,可作为该场景下的辅助能力补充。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install daily-strava-roast;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

daily-strava-roast 怎么安装?

在终端执行 openclaw skills install daily-strava-roast。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

daily-strava-roast 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

daily-strava-roast 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

daily-strava-roast 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

daily-strava-roast 用的人多吗?

公开数据是累计安装 6,106 次,近一周安装 257 次,下载 2,138 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

daily-strava-roast 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理效率类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
daily-strava-roast

每日斯特拉瓦烤肉 · 本页

6,106—接触敏感数据MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
daily-strava-roast
description
Generate a playful or sharp daily roast of recent Strava activity. Use when asked to roast, recap, tease, or humorously summarize a Strava workout or a recent day of training. Useful for scheduled daily activity roasts, playful fitness summaries, or lightly sarcastic post-workout commentary. Prefer the deterministic package/script for data prep and fallback; when running inside OpenClaw, use the connected/default runtime model only for the final paragraph if available, then fall back to the deterministic roast path on failure.

Daily Strava Roast

Use this skill to turn recent Strava activity into a short roast-style summary.

Default workflow

  1. Use the deterministic implementation first to fetch and summarize activity.
  2. If you are inside OpenClaw and want the V2 path, use the structured context/prompt output as model input for the final paragraph only.
  3. If connected-model generation is unavailable or weak, fall back to the deterministic roast output.
  4. Do not pretend the standalone Python package has a built-in OpenClaw connected-model API if it does not.

What this skill does

This skill provides:

  • deterministic Strava fetch + summary tooling
  • adjustable tones and spice levels
  • V1 roast fallback that is stable and testable
  • V2 context/prompt building for better final-paragraph generation in the OpenClaw runtime

Preferred commands

Use the packaged CLI for deterministic preparation and fallback:

uv run --project {baseDir} daily-strava-roast summary --json --pretty
uv run --project {baseDir} daily-strava-roast context --pretty
uv run --project {baseDir} daily-strava-roast prompt
uv run --project {baseDir} daily-strava-roast roast

Do not rely on the removed legacy script path. Use the packaged CLI commands only.

Runtime guidance

When invoked inside OpenClaw for an actual roast reply:

  • run deterministic preparation first
  • use the connected/default runtime model only to write the final roast paragraph
  • keep that paragraph to one short paragraph
  • do not invent stats
  • if generation fails, return the deterministic roast instead of erroring

Runtime recipe

Use this sequence:

  1. Build context JSON:
uv run --project {baseDir} daily-strava-roast context --pretty
  1. Build the constrained prompt:
uv run --project {baseDir} daily-strava-roast prompt
  1. Ask the connected/default OpenClaw runtime model to write the final paragraph from that prompt.
  2. Before replying, sanity-check the generated paragraph:

- exactly one paragraph - one or two sentences max unless unusually short - no bullet points - no invented stats - no stat dump; usually no more than two concrete metrics unless a third really earns its place - not generic AI filler - avoids banned phrases, stale identity/relationship jokes, pet phrases, and over-clever wording - avoids poetic or cosmic phrasing - tone matches requested spice/tone closely enough

  1. If the paragraph fails those checks or generation is unavailable, fall back to:
uv run --project {baseDir} daily-strava-roast roast

Fallback triggers

Fall back immediately if any of these happen:

  • no connected/default runtime model is available
  • generated output is empty
  • generated output invents numbers, activities, or claims not present in the prompt/context
  • generated output is multiple paragraphs or list-like
  • generated output crams in too many stats without real comedic payoff
  • generated output uses banned phrases or obvious close variants
  • generated output leans on stale identity, relationship, or defining-trait jokes
  • generated output leans on polished LLM-clever wording instead of dry mockery
  • generated output drifts into poetic, cosmic, or overly ornate phrasing
  • generated output is obviously generic, repetitive, or less readable than the deterministic roast

When falling back:

  • do not apologize unless the user needs to know
  • just return the deterministic roast text

When working purely from the repo/CLI:

  • treat connected-model generation as a runtime concern, not a packaged-CLI feature
  • keep the deterministic path working without extra runtime dependencies

Inputs

By default the skill reads Strava app config from:

~/.openclaw/secure/strava_app.json

And by default the token file is:

~/.openclaw/workspace/agents/tars-fit/strava_tokens.json

Normal auth behaviour:

  • treat ~/.openclaw/secure/strava_app.json as the canonical app-credentials source
  • if setup already exists, expired access tokens should refresh automatically using the refresh token
  • if Strava still returns 401, retry once after a forced refresh
  • if the token file is missing, invalid, or missing required fields, treat that as initial setup required and tell the user clearly
  • if the token file exists but app credentials are missing or incomplete, return config_incomplete clearly
  • if setup exists but refresh/reauthorisation is needed, return the reauth-required path instead of pretending it is a rest day
  • avoid depending on sourced shell profiles for routine auth

Use this to inspect auth readiness:

uv run --project {baseDir} daily-strava-roast auth-url

Use JSON mode when another agent needs machine-readable status:

uv run --project {baseDir} daily-strava-roast roast --json --pretty

Tones

Supported tones:

  • dry
  • playful
  • savage
  • coach

Spice

Spice controls roast intensity:

  • 0 — gentle
  • 1 — light tease
  • 2 — proper roast
  • 3 — scorched earth

References

Read as needed:

  • references/design.md for roast heuristics and failure cases
  • docs/V2.md for the V2 architecture and package/runtime boundary

平台分布

OpenClaw

71.77%
按下载量换算1,534

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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