bear-research-enricher
/install bear-research-enricher
Research Assistant
Read Bear notes tagged 「待整理」, extract key topics, search for matching GIFs via gifgrep, and insert them inline. When done, remove the 「待整理」 tag and add 「已整理」.
Prerequisites
- Bear app running on macOS with a valid API token at
~/.config/grizzly/token grizzlyCLI installed (go install github.com/tylerwince/grizzly/cmd/grizzly@latest)gifgrepskill installed (provides GIF search)curlavailable
Workflow
- Fetch notes: Run
grizzly open-tag --name "待整理" --enable-callback --json --token-file ~/.config/grizzly/tokento list all notes with the tag. - For each note:
a. Read note content via
grizzly open-note --id \x3CNOTE_ID> --enable-callback --json --token-file ~/.config/grizzly/tokenb. Extract 2–3 key topics or keywords from the note title and first paragraph. c. For each keyword, search GIFs using the gifgrep skill (orcurl "https://api.giphy.com/v1/gifs/search?api_key=dc6zaTOxFJmzC&q=\x3Ckeyword>&limit=3"as fallback). d. Pick the most relevant GIF URL per keyword. e. Append GIFs to the note usinggrizzly add-text:echo -e "\
---
" | grizzly add-text --id \x3CNOTE_ID> --mode append --token-file ~/.config/grizzly/token
```
3. Retag: Remove 「待整理」 and add 「已整理」 by updating note tags via Bear's x-callback-url:
open "bear://x-callback-url/add-tag?id=\x3CNOTE_ID>&name=已整理"
open "bear://x-callback-url/remove-tag?id=\x3CNOTE_ID>&name=待整理"
- Report: Summarize which notes were enriched and how many GIFs were added.
Script
For batch processing, use scripts/enrich_notes.sh:
bash scripts/enrich_notes.sh
The script handles the full loop: fetch tagged notes → per-note topic extraction → GIF search → insert → retag.
Notes
- If no notes carry the 「待整理」 tag, report that and exit.
- If GIF search returns no results for a keyword, skip that keyword rather than inserting a placeholder.
- Bear must be running; grizzly commands will fail silently otherwise.
- Rate-limit GIF API calls (1 request/second) to avoid throttling.
- 确保已安装 OpenClaw(本地或 Docker 部署)
- 在对话框中输入安装命令:
/install bear-research-enricher - 安装完成后,直接呼叫该 Skill 的名称或使用
/bear-research-enricher触发 - 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
bear-research-enricher 是什么?
Enrich Bear research notes tagged 「待整理」 with thematic GIFs. Use when the user wants to auto-illustrate or spruce up draft research notes in Bear, or mentions... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 49 次。
如何安装 bear-research-enricher?
在 OpenClaw 或 Claude Code 对话框中运行命令「/install bear-research-enricher」即可一键安装,无需额外配置。
bear-research-enricher 是免费的吗?
是的,bear-research-enricher 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。
bear-research-enricher 支持哪些平台?
bear-research-enricher 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。
谁开发了 bear-research-enricher?
由 terrycarter1985(@terrycarter1985)开发并维护,当前版本 v0.1.0。