cubox-research
Search a user's Cubox collection deeply by topic, theme, or question.
Skill by jtsang4
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/jtsang4-cubox-research
Asks which of your tools to add it to (Claude Code, Codex, Cursor, VS Code, Windsurf, Gemini CLI, Claude Desktop) and shows the change first. See https://agentmart.dev/cli.
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About
Use cases: documents, frontend, writing, research
Reviews
Write a reviewNo reviews yet. Installed it? Reviews come from verified installers only. How reviews work
Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
- Runs as
- Node.js package
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/cubox-research
What's inside
- Skill name
cubox-research- Description
- Search a user's Cubox collection deeply by topic, theme, or question. Use this whenever the user asks to search Cubox, saved articles, archived reads, or collected pages for a subject, wants multiple keyword variations tried, wants full-text search across Cubox, or needs article details exported from Cubox HTML into local Markdown with downloaded images for later analysis.
- License
- MIT
- Compatibility
- Requires Bun, network access, and a configured `.env` file in this skill directory.
- Instructions
- 180 lines in SKILL.md · view on GitHub
Before installing
- Ships executable scripts
Files (9)
- .env.example
- .gitignore
- SKILL.md
- bun.lock
- evals.json · evals/
- package.json
- api-map.md · references/
- cubox.ts · scripts/
- inspect-har.ts · scripts/
SKILL.md (first lines)
# cubox-research Use this skill when the user's Cubox collection is the source of truth. The goal is not to do one shallow keyword lookup, but to search broadly, vary keywords on purpose, fetch the best-matching article details, and analyze local Markdown instead of raw Cubox HTML. ## Preflight 1. Work from this skill directory. 2. Make sure dependencies are installed once with `bun install`. 3. Check `.env` before any API call. The only required value is `CUBOX_AUTHORIZATION`. 4. Prefer read-only endpoints. Do not call mutation endpoints such as `POST /c/api/norm/card/read` unless the user explicitly asks for that side effect. ## What The Bundled Scripts Do - `scripts/cubox.ts context` Fetches account search context: groups, tags, and the overloaded `keyword/list` payload. - `scripts/cubox.ts search` Runs multiple keywords across `preview`, `quick`, and `full-text` modes, then deduplicates and ranks hits. - `scripts/cubox.ts research` Does the same search workflow and also fetches article details for the strongest matches. - `scripts/cubox.ts fetch-detail` Fetches one Cubox article detail, converts the HTML fragment to Markdown, downloads images locally, and stores the files in the temp collection. - `scripts/inspect-har.ts` Re-summarizes a HAR file into a quick API map when the user provides a fresh capture. ## Core Working Style Treat Cubox retrieval like library research: 1. Understand the user's actual topic or question. 2. Build a keyword set with deliberate variation. 3. Search in more than one mode. 4. Fetch article details for the best candidates. 5. Analyze the exported Markdown and cite local file paths. Do not stop after the first hit unless the user explicitly wants a quick lookup. ## Keyword Planning Before searching, create a keyword set that covers multiple angles: - The direct topic phrase - Synonyms or alternate wording - English and Chinese variants when relevant - Product names, author names, company names, or framework names tied to the topic - Abbreviations and shorthand terms - Narrower subtopics if the topic is broad Good example for a topic like "agent harness": - `agent harness` - `harness engineering` - `deep agents` - `agent evals` - `skills` - `工具调用` - `智能体评测` If the user already gives candidate terms, still add 2-4 meaningful variations unless doing so would obviously introduce noise. ## Retrieval Workflow ### 1. Optional context pass When tags, collections, or browsing context might help, run: ```bash bun run ./scripts/cubox.ts context --json ``` Use it to understand available groups and tags before searching. ### 2. Run broad search Use `research` when you want one command to search and fetch details: ```bash bun run ./scripts/cubox.ts research \ --topic "agent harness" \ --keyword "agent harness" \ --keyword "harness engineering" \ --keyword "deep agents" \ --keyword "智能体评测" \ --detail-limit 5 \ --json ``` Use `search` when you want to inspect candidates before downloading details: ```bash bun run ./scripts/cubox.ts search \ --topic "台积电营收模型" \ --keyword "台积电" \ --keyword "TSMC" \ --keyword "营收模型" \ --keyword "equity research" \ --json ``` Default behavior searches all three modes: - `preview`: quick prefix discovery and highlighted matches - `quick`: title and metadata-oriented retrieval - `full-text`:正文全文搜索 ### 3. Fetch the strongest candidates When you already know the `cardId`, fetch a single article: ```bash bun run ./scripts/cubox.ts fetch-detail --card-id 7433881606177162362 --json ``` The exported files are stored under: ```text <system temp>/cubox-collection/<cardId>-<safe-title>/ ``` Each article directory contains:
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Signals
- Stars
- 2
- Forks
- 0
- Open issues
- 0
- Last commit (this folder)
- Mar 21, 2026 (7 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Repository
- github.com/jtsang4/efficient-coding
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
cubox-research skill. Agent Mart. https://agentmart.dev/skills/jtsang4-cubox-research (last updated 2026-10-24)