據 AlphaMoat 統計,截至 2026-09,Research Tracker 累計下載 4,152 次、獲 1 個星標,在全部 5,078 個 AI 技能中排名第 2,421 位,在「AI 智慧體」分類(969 個)中排名第 474 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 135 | 3905 | 1 | - |
| SkillHub ↗ | 135 | 4152 | 1 | — |
各平台的計數口徑不同,統計時間不一致。
該CLI支援建立研究專案、記錄步驟進度、傳送指令或停止訊號、檢視狀態與上下文,並歸檔或完成專案。事件日誌採用追加方式,資料庫儲存在本地。它依賴第三方CLI,安裝前應核實來源並優先使用固定版本;適合需要持續專案狀態和交接管理的長期研究工作,不是普通一次性搜尋的必需工具。
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 | 4152 | — | 1 |
| 2026-08 | 3871 | +3.0% | 1 |
| 2026-07 | 3759 | +6.0% | 1 |
| 2026-06 | 3546 | +2.8% | 1 |
| 2026-05 | 3449 | — | 1 |
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: research-tracker description: Manage autonomous AI research agents with SQLite-based state tracking. Use when spawning long-running research sub-agents, tracking multi-step investigations, coordinating agent handoffs, or monitoring background work. Triggers on: research projects, sub-agent coordination, autonomous investigation, progress tracking, agent oversight. --- # Research Tracker CLI tool for managing autonomous research agents with append-only state, instruction queues, and oversight. ## Prerequisites
```bash
brew tap 1645labs/tap
brew install julians-research-tracker
```
Or: `go install github.com/1645labs/julians-research-tracker/cmd/research@latest`
## Quick Start
### Start a research project
```bash
research init market-q1 --name "Q1 Market Analysis" --objective "Analyze competitor pricing and positioning"
```
### As the research agent — log progress
```bash
export RESEARCH_SESSION_ID="$SESSION_KEY" # Track which agent is writing
research log market-q1 STEP_BEGIN --step 1 --payload '{"task":"gather sources"}'
# ... do work ...
research log market-q1 STEP_COMPLETE --step 1
research heartbeat market-q1
```
### Check status (from main session or heartbeat)
```bash
research status market-q1 --json
research context market-q1 --last 5 # Truncated context for prompts
```
### Send instructions to running agent
```bash
research instruct market-q1 "Focus on enterprise segment" --priority URGENT
research stop-signal market-q1 # Request graceful stop
```
### Agent checks for instructions
```bash
research pending market-q1 --json
research ack market-q1 --all # Acknowledge after processing
research check-stop market-q1 # Exit 0 = stop, Exit 1 = continue
```
## Commands Reference
| Command | Purpose |
|---------|---------|
| `init <id> -o "..."` | Create project with objective |
| `list [--status active\|done\|all]` | List projects (includes `needs_attention` flag) |
| `show <id>` | Project details + recent events |
| `stop <id>` | Stop project, send STOP instruction |
| `archive <id>` | Archive completed project |
| `log <id> <event> [--step N]` | Log event (STEP_BEGIN, CHECKPOINT, BLOCKED, etc.) |
| `heartbeat <id>` | Update alive timestamp |
| `block <id> --reason "..."` | Mark blocked, needs input |
| `complete <id>` | Mark done |
| `status <id> [--json]` | Current state summary |
| `context <id> [--last N]` | Truncated context for agent prompts |
| `instruct <id> "text"` | Send instruction |
| `pending <id>` | List unacked instructions |
| `ack <id> [--all]` | Acknowledge instructions |
| `check-stop <id>` | Exit code: 0=stop, 1=continue |
| `audit <id> --verdict pass\|drift` | Log audit result |
## Event Types
`STARTED`, `STEP_BEGIN`, `STEP_COMPLETE`, `CHECKPOINT`, `BLOCKED`, `UNBLOCKED`, `AUDIT_PASS`, `AUDIT_DRIFT`, `HEARTBEAT`, `DONE`, `STOPPED`, `TIMEOUT`
## Integration Pattern
### Spawning a research agent
```
1. research init <project> --objective "..."
2. sessions_spawn with task including:
- Project ID and objective
- Instructions to use research CLI for state
- Check stop signal before each step
- Log progress with heartbeat
3. Heartbeat monitors: research list --json | check needs_attention
4. Send instructions via: research instruct <project> "..."
```
### Agent loop (in spawned agent)
```bash
while research check-stop $PROJECT; [ $? -eq 1 ]; do
research pending $PROJECT --json # Check instructions
research log $PROJECT STEP_BEGIN --step $STEP
# ... do work ...
research log $PROJECT STEP_COMPLETE --step $STEP
research heartbeat $PROJECT
STEP=$((STEP + 1))
done
research complete $PROJECT
```
## Attention Detection
`research list --json` includes `needs_attention: true` when:
- Last event is BLOCKED
- Has unacked URGENT or STOP instructions
- Heartbeat stale (>5 min since last HEARTBEAT event)
- Last audit was AUDIT_DRIFT
## Database
SQLite at `~/.config/research-tracker/research.db` (WAL mode, append-only events).
Run `research db migrate` after install. Schema auto-migrates on first use.
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。