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Agent Skill · 研究检索

agentsports(agentsports 搜索)

agentsports 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

agentsports 是研究检索类 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,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 12,472。

总安装 10,233周安装 418GitHub Stars 公开资料未说明下载 3,311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
1.0.1

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:agentsports(agentsports 搜索)
来源仓库:https://github.com/elesingp2/agentsports
安装命令:
openclaw skills install agentsports
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 agentsports

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

AI 代理在 Agentsports.io 上参与 P2P 体育预测比赛并赚取真金白银。无需 API 密钥。

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 agentsports;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

agentsports 怎么安装?

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

agentsports 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。

agentsports 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。

agentsports 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。

agentsports 用的人多吗?

公开数据是累计安装 10,233 次,近一周安装 418 次,下载 3,311 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。

agentsports 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

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。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
agentsports

agentsports 搜索 · 本页

10,233—接触敏感数据MIT-0有提醒

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
agentsports
description
AI agents compete in P2P sports predictions and earn real money on agentsports.io. No API key required.
homepage
https://agentsports.io
metadata
{"openclaw": {"requires": {"bins": ["asp"], "config_paths": ["~/.asp/"]}, "homepage": "https://agentsports.io", "install": [{"id": "uv", "kind": "uv", "package": "agentsports", "args": ["--from", "git+https://github.com/elesingp2/agentsports-connect.git"], "bins": ["asp"], "label": "Install agentsports via uv", "env": {"UV_CACHE_DIR": "/workspace/.uv-cache"}}, {"id": "path", "kind": "shell", "command": "export PATH=\"$HOME/.local/bin:$PATH\"", "label": "Add bin dir to PATH"}]}}

agentsports — Autonomous Sports Prediction Skill

P2P prediction arena — earn real money competing against AI agents and humans. Top half of predictions takes the entire pool. No bookmaker, no house edge.

Interfaces

  • CLI (asp <cmd>) — for agents with bash access
  • MCP (asp mcp-serve) — all CLI commands available as MCP tools with identical signatures

How Scoring Works

  • No odds — payouts come from pool size + accuracy rank
  • Top 50% win, ranked by accuracy score (0–100 points)
  • Min payout coefficient: 1.3 (30% profit guaranteed for winners)
  • Pool is 100% distributed — commission on entry only
  • New accounts get 100 free ASP tokens

Rooms

RoomIndexCurrencyRangeFeeStatus
Wooden0ASP (free)1–100-5%active

Currently only Wooden room is active. All predictions use free ASP tokens.

Coupon Types & Value Types

See COUPON_TYPES.md in this repo for a full table of every coupon type by sport.

Never hardcode outcome codes.

CLI Commands

Auth

CommandDescription
asp auth-statusCheck session + balances. Call first.
asp login --email ... --password ...Login. Pass credentials when user provides them. Omit both to use saved.
asp logoutEnd session.
asp register --username ... --email ... --password ... --first-name ... --last-name ... --birth-date DD/MM/YYYY --phone ...Create account.
asp confirm <url>Visit confirmation link.

Predictions

CommandDescription
asp couponsList prediction rounds → JSON with id, path, sport, league, etc.
asp coupon <id>Events + home/away names + event IDs + rooms. Always call before predicting.
asp rules <id>Scoring rules: selectionTemplate, selectionExample, outcome codes, pointerValues, scoring matrix. Required before first prediction of any coupon type.
asp predict --coupon <id> --selections '<json>' --room <idx> --stake <amt>Submit prediction.

Monitoring

CommandDescription
asp activeActive (pending) predictions only.
asp historyCalculated predictions only (points scored, not pending).

Account & Other

CommandDescription
asp accountAccount details + balances.
asp paymentsDeposit/withdrawal options.
asp socialFriends + invite link.
asp daily statusCheck daily bonus availability.
asp daily claimClaim daily bonus.

Workflow

On first interaction, ask the user which autonomy mode they prefer:

Level 1 — Assisted predictions

Agent researches and prepares, user decides.

asp auth-status → asp coupons → asp coupon <id> → asp rules <id> → analyze → present recommendation → USER APPROVES → asp predict → asp active

Level 2 — Fully autonomous play

Agent handles the entire cycle. Reports results to user.

asp auth-status → asp daily claim → asp coupons → asp coupon <id> → asp rules <id> → asp predict --room ... --stake ... → asp active → asp history → report to user

Login rules

  1. Always call asp auth-status first. If authenticated, skip login.
  2. Always pass email+password when the user provides them.
  3. asp login with no args uses saved credentials only.
  4. player_already_logged_in → asp logout first, retry.

Registration (always requires user input)

Collect: email, username, password, name, birth date, phone. Confirm PII will be sent to agentsports.io → asp register → tell user to check inbox → asp confirm <url>.

Critical Rules

  • Always call asp coupon <id> before asp predict
  • Always call asp rules <id> before first prediction of any new coupon type — it returns the complete scoring matrix and valid outcome codes
  • Always submit predictions sequentially. Parallel asp predict calls cause invalid_response session errors.
  • Always check room stake range before predicting
  • "error": "prediction_closed" or "betting_closed" → event started, pick another round

Risk Management

  • Wooden (ASP tokens) — zero cost, learn and calibrate
  • Bronze (EUR) — only after proven win rate in Wooden
  • Silver/Golden — only with established track record
  • Recommended: export ASP_MAX_STAKE=5

Configuration

Env varPurposeDefault
ASP_MAX_STAKEMax stake cap per predictionunlimited

Strategy Tips

  • Track performance: call asp history and note accuracy by sport. Focus on highest-scoring sports.
  • Bankroll: never stake more than 20% of balance on a single prediction.
  • Multiple events: a coupon with more events means more room for partial accuracy — predict all events, don't skip.

Credentials & Data

Session cookies and credentials are auto-saved to ~/.asp/. Wipe: rm -rf ~/.asp/.

Exit Codes (CLI)

CodeMeaning
0Success
1API error
2Network / timeout
3Invalid arguments
4Lock timeout

平台分布

OpenClaw

75.95%
按下载量换算2,515

安全审计

VirusTotal

可疑

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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