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terrycarter1985

bear-research-enricher

作者 terrycarter1985 · GitHub ↗ · v0.1.0 · MIT-0
cross-platform ✓ 安全检测通过
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在 OpenClaw 中安装
/install bear-research-enricher
功能描述
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...
使用说明 (SKILL.md)

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
  • grizzly CLI installed (go install github.com/tylerwince/grizzly/cmd/grizzly@latest)
  • gifgrep skill installed (provides GIF search)
  • curl available

Workflow

  1. Fetch notes: Run grizzly open-tag --name "待整理" --enable-callback --json --token-file ~/.config/grizzly/token to list all notes with the tag.
  2. For each note: a. Read note content via grizzly open-note --id \x3CNOTE_ID> --enable-callback --json --token-file ~/.config/grizzly/token b. Extract 2–3 key topics or keywords from the note title and first paragraph. c. For each keyword, search GIFs using the gifgrep skill (or curl "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 using grizzly add-text:
    echo -e "\
    

---
\x3Ckeyword>" | 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"
  1. 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.
安全使用建议
This skill is reasonable for its stated purpose, but use it carefully: make sure the 「待整理」 tag is only on notes you want changed, back up important Bear notes first, and avoid running it on private or sensitive research if you do not want note topics sent to Giphy.
功能分析
Type: OpenClaw Skill Name: bear-research-enricher Version: 0.1.0 The skill automates enriching Bear notes with GIFs by extracting keywords from note content and searching Giphy. It utilizes the legitimate 'grizzly' CLI tool and Bear's native x-callback-url scheme for note manipulation. All behaviors, including accessing the Bear API token at ~/.config/grizzly/token and sending extracted keywords to the Giphy API, are transparently documented and strictly aligned with the stated purpose in SKILL.md and scripts/enrich_notes.sh.
能力标签
requires-sensitive-credentials
能力评估
Purpose & Capability
The Bear note reading, GIF lookup, insertion, and retagging behavior is coherent with the stated purpose of enriching notes tagged 「待整理」.
Instruction Scope
The workflow is scoped to notes with the 「待整理」 tag, but it processes all matching notes in a batch and does not ask for per-note confirmation.
Install Mechanism
There is no install spec, while the documentation expects user-installed tools such as grizzly, gifgrep, curl, and a Bear token file; grizzly is suggested via an unpinned @latest install command.
Credentials
The required Bear token and Giphy network calls are purpose-aligned, but users should understand that Bear note content is accessed locally and derived keywords are sent to an external GIF API.
Persistence & Privilege
The skill makes persistent edits to Bear notes by appending GIF markdown and changing tags; no hidden background persistence or self-start behavior is shown.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install bear-research-enricher
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /bear-research-enricher 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v0.1.0
Initial release: auto-enrich Bear research notes tagged 待整理 with thematic GIFs
元数据
Slug bear-research-enricher
版本 0.1.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

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。

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