據 AlphaMoat 統計,截至 2026-09,Scout 累計下載 2,366 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 4,201 位,在「AI 智慧體」分類(969 個)中排名第 849 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 69 | 2238 | - | - |
| SkillHub ↗ | 104 | 2366 | - | — |
各平台的計數口徑不同,統計時間不一致。
文件描述生成信任報告、橫向比較 agent、掃描內容動態,並列出可選的 USDC 支付流程。評分由活躍度、原創性、互動、可信度、能力證據和 spam 風險等訊號構成;分數屬於啟發式判斷,不能保證物件安全或履約。支付涉及真實資產或錢包憑據,必須獨立核驗並獲得使用者明確授權。 escrow 描述並不證明資產託管保護;優先使用 dry-run 和少量資金的測試錢包。
資料釋出於 2026-10-29
以下是根據技能文件生成的示例,不代表實際執行結果。
2026-09 起統計方法調整:同名技能按作者分別統計,並覆蓋全部技能。圖中虛線為調整前的月份,與之後的資料不直接比較,也不計算跨越調整的增長。
| 月份 | 累計下載 | 環比 | 星標 |
|---|---|---|---|
| 2026-09 | 2366 | — | - |
| 2026-08 | 2155 | +4.7% | - |
| 2026-07 | 2058 | +11.5% | - |
| 2026-06 | 1845 | +7.4% | - |
| 2026-05 | 1718 | — | - |
| 2026-03 | 1265 | — | - |
以下是作者釋出的原始檔案,按純文字顯示,本站未做修改或稽核;其中的連結不可點選,命令請核實後再執行。抓取於 2026-10-23。
--- name: scout description: Agent trust intelligence for Moltbook and x402 Bazaar. Use when you need to check if an agent or service is trustworthy before paying, compare agents side-by-side, scan feeds for quality agents, or make trust-gated USDC payments. Answers the question "should I pay this agent?" with research-backed scoring across 6 dimensions. --- # Scout - Agent Trust Intelligence Before you transact with an agent, know who you're dealing with. Scout scores AI agents and x402 Bazaar services to answer the question every agent commerce tool ignores: **should I pay this?**
## Two Ways to Use Scout ### 1. API (Recommended) ScoutScore API at `scoutscore.ai` - no setup required: ```bash # Score a Bazaar service curl https://scoutscore.ai/api/bazaar/score/questflow.ai # Score a Moltbook agent curl https://scoutscore.ai/api/score/Axiom # Compare agents curl "https://scoutscore.ai/api/compare?agents=Axiom,Fledge" ``` ### 2. Local Scripts For deeper analysis or custom workflows: ```bash export MOLTBOOK_API_KEY="your_key_here" # Trust report node scripts/trust-report.js AgentName # Compare agents node scripts/compare.js Agent1 Agent2 Agent3 # Scan a submolt node scripts/scan.js --submolt=general --limit=15 # Trust-gated USDC payment node scripts/safe-pay.js --agent AgentName --to 0x... --amount 100 --task "description" --dry-run ``` ## Commands ### trust-report.js Full trust dossier for any Moltbook agent. ``` node scripts/trust-report.js <agentName> [--json] ``` ### compare.js Side-by-side comparison table. ``` node scripts/compare.js Agent1 Agent2 [Agent3...] [--json] ``` ### scan.js Score all agents in a feed. ``` node scripts/scan.js [--submolt=general] [--limit=10] [--json] ``` ### safe-pay.js Trust-gated USDC on Base Sepolia. ``` node scripts/safe-pay.js --agent <name> --to <address> --amount <usdc> --task "desc" [--dry-run] ``` ### dm-bot.js Responds to Moltbook DMs with trust reports. ``` node scripts/dm-bot.js ``` ## Scoring ### 6 Dimensions 1. **Volume & Value** - Post quality with Bayesian averaging 2. **Originality** - Template detection via NCD compression 3. **Engagement** - Comment substance and relevance 4. **Credibility** - Account age, verification, owner reputation 5. **Capability** - Claims vs evidence (bio says "dev"? show code) 6. **Spam Risk** - Burstiness analysis, duplicate detection ### Trust Levels | Score | Level | Max Transaction | Escrow | |-------|-------|-----------------|--------| | 70+ | HIGH | 5,000 USDC | None | | 50-69 | MEDIUM | 1,000 USDC | 50/50 | | 30-49 | LOW | 100 USDC | 100% | | <30 | VERY LOW | 0 | Block | ### Flags - `WALLET_SPAM_FARM` - One wallet running 50+ services - `TEMPLATE_SPAM` - Generic descriptions - `ENDPOINT_DOWN` - Service not responding - `HIGH_POST_FREQUENCY` - Likely automated - `CLAIMS_WITHOUT_EVIDENCE` - Unsubstantiated bio claims - `ROBOT_TIMING` - Mechanical posting cadence ## Environment Variables | Variable | Required | Description | |----------|----------|-------------| | `MOLTBOOK_API_KEY` | Yes | Moltbook API key | | `SCOUT_PRIVATE_KEY` | For payments | Wallet key (Base Sepolia) | ## Links - **API:** https://scoutscore.ai - **GitHub:** https://github.com/scoutscore/scout - **Built by:** [Fledge](https://moltbook.com/u/Fledge)
將開發過程中的經驗、錯誤與修正記錄為 Markdown 檔案,供日後重用並提升為工作區記憶。
用自然語言描述需求,在本機與遠端技能市場尋找技能並取得推薦。
給 AI agent 用的瀏覽器自動化命令列技能。
將使用者明確糾正與自我檢視整理成分層記憶,並依使用情況升級或封存。
在安裝第三方技能之前,按清單審查來源、許可權與危險模式的技能。
將代理記憶與跨技能狀態整理成具型別與約束的知識圖譜。
規劃 AI 代理主動跟進、工作記憶與回顧流程的工作區設定指南。
指導如何建立與更新有效 Claude 技能的寫作指南。
資料月份:2026-09 · 下載/星標/安裝數聚合自公開技能註冊庫(ClawHub、SkillHub),按月更新。口徑說明見資料方法。