據 AlphaMoat 統計,截至 2026-09,swiftscholar-skill 累計下載 1,989 次、獲 0 個星標,在全部 5,078 個 AI 技能中排名第 4,437 位,在「專業領域」分類(465 個)中排名第 387 位。
| 平台 | 累計安裝 | 累計下載 | 星標 | 評論 |
|---|---|---|---|---|
| ClawHub ↗ | 58 | 1989 | - | - |
| SkillHub ↗ | 167 | 1973 | - | — |
各平台的計數口徑不同,統計時間不一致。
該技能可執行關鍵詞或語義檢索,提交 PDF 或網址進行解析,取得分析結果,並查看收藏與帳戶使用情況。呼叫需要 API 金鑰;上傳論文、網址或筆記可能向服務傳送私人研究資料,提交解析或儲存收藏也可能消耗額度或改變資料庫,應在執行前確認。 優先使用 /api/tools/* 並核實必填參數;介面失敗時應回報,確認解析完成後再取得分析結果。
資料釋出於 2026-10-27
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 | 1989 | — | - |
| 2026-08 | 1894 | +6.3% | - |
| 2026-07 | 1782 | +15.3% | - |
| 2026-06 | 1545 | +8.6% | - |
| 2026-05 | 1423 | — | - |
| 2026-03 | 1097 | — | - |
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: swiftscholar-skill description: Integrates the SwiftScholar HTTP API for searching, submitting, and analyzing academic papers. Use when the user wants to search literature, submit PDFs/URLs for parsing, retrieve analyses, manage favorites, or inspect SwiftScholar account usage programmatically. --- # SwiftScholar Skill (`swiftscholar-skill`) This skill enables the agent to use the **SwiftScholar HTTP API** to search, submit, analyze, and manage academic papers. Prefer the JSON-first `/api/tools/*` endpoints instead of deprecated `/api/mcp/tools/*` endpoints.
Basic information:
- **Base URL**: `https://www.swiftscholar.net`
- **Auth**: `Authorization: Bearer <API_KEY>`
- **Spec version**: OpenAPI 3.1.0 (`SwiftScholar HTTP API 1.0.0`)
> Never expose the API key in natural language responses; only include it in actual HTTP headers.
---
## 1. When to use this skill
Use the SwiftScholar API in these situations:
- The user wants to:
- **search academic papers** (keyword or semantic/vector search)
- **submit paper URLs / PDFs** for parsing
- **retrieve structured markdown analysis** or raw markdown
- **manage / inspect favorites and favorite folders**
- **inspect parse quotas, usage, and available analysis models**
Typical trigger phrases (examples):
- “literature search”, “keyword search paper”, “semantic search paper”
- “parse this paper PDF/URL”, “analyze this paper”
- “get detailed analysis / markdown for this paper”
- “SwiftScholar favorites / favorite folders”
- “SwiftScholar account usage / quota / parse history”
---
## 2. Authentication and calling conventions
### 2.1 Authentication
- All `/api/tools/*` endpoints use **Bearer tokens**:
- Header: `Authorization: Bearer <SWIFTSCHOLAR_API_KEY>`
- The agent must not reveal or infer the key in natural language responses.
### 2.2 General request conventions
- **HTTP method**: all tool endpoints are `POST`.
- **Content-Type**:
- JSON requests: `application/json`
- PDF upload: `multipart/form-data` with `file` as binary PDF
- **Error handling**:
- JSON responses follow the `ToolApiResponse` structure:
- `ok: boolean` (always present)
- `data: object` (present on success)
- `error: string` (may be present on failure)
- After a call:
- If `ok == false` or `error` is present, briefly explain the failure to the user and suggest next steps (e.g., adjust parameters, narrow filters).
---
## 3. Core capabilities and endpoints
This section is organized by **capability**, not by URL, to help the agent choose appropriate tools.
All listed endpoints live under `paths./api/tools/...`.
### 3.1 Paper tags and basic browsing
1. **List all paper tags (with IDs and usage counts)**
- Endpoint: `POST /api/tools/paper_tags_list`
- Body: `{}` (no parameters)
- Purpose:
- When recommending tag filters or constructing complex queries, first list available tags and their IDs.
2. **Paginate accessible papers**
- Endpoint: `POST /api/tools/papers_paginate`
- Body fields (partial):
- `page: integer >= 1` (default 1)
- `pageSize: integer 1–50` (default 10)
- `licenses: string[]` (may include `'none'`)
- `publishedFrom: string (YYYY-MM-DD)`
- `publishedTo: string (YYYY-MM-DD)`
- Purpose:
- Browse paper lists by time or license as a base for search results or user-library browsing.
### 3.2 Search: keyword search vs vector (semantic) search
1. **Keyword search (literal string matching)**
- Endpoint: `POST /api/tools/papers_search_keyword`
- Key body fields:
- `query: string` (required; search string)
- `page, pageSize` (same semantics as `papers_paginate`)
- `tags: string[]` / `tagNames: string[]` (tag filters)
- `tagMode: "and" | "or"` (default `"or"`)
- `licenses, publishedFrom, publishedTo` (same as above)
- Usage guidance:
- Prefer this when the user provides explicit keywords, title fragments, or phrases.
- Explain that this is **literal matching**, ideal for precise lookup.
2. **Vector search (semantic search)**
- Endpoint: `POST /api/tools/papers_search_vector`
- Key body fields:
- `query: string` (required; natural-language query)
- `limit: integer 1–30` (default 10)
- Other filters as in `papers_search_keyword`
- Usage guidance:
- Use when the user describes **fuzzy concepts**, research themes, or questions (e.g., “recent progress of LLMs in medical imaging”).
- Clarify that this is **semantic search**, better for “finding related papers” without exact title matches.
### 3.3 Submitting papers: URL / PDF / batch URLs
1. **Submit a paper by URL**
- Endpoint: `POST /api/tools/paper_submit_url`
- Body fields:
- `url: string` (required; paper source page or PDF URL)
- `modelId: string` (optional; PDF analysis model)
- `force: boolean` (force re-parse)
- `favoriteFolderId: string | null` (favorites folder, `null` for root)
- `favoriteNote: string` (favorites note)
- Usage guidance:
- Use when the user provides a paper page URL or direct PDF URL and wants parsing, analysis, or saving to favorites.
- Mention that parsing may take time and suggest how to check results later if needed.
2. **Submit or link a PDF file**
There are two main modes:
- JSON API:
- Endpoint: `POST /api/tools/paper_submit_pdf`
- JSON body:
- `pdfUrl: string` OR `pdfBase64: string` (one of them is required)
- `fileName: string` (optional)
- Other fields as in `paper_submit_url` (`modelId`, `force`, `favoriteFolderId`, `favoriteNote`)
- Note: the spec explicitly says “provide either `pdfUrl` or `pdfBase64`.”
- Multipart upload:
- Same endpoint with `multipart/form-data`:
- `file: binary` (required; PDF file content)
- Optional: `modelId`, `force`, `favoriteFolderId`, `favoriteNote`
- Usage guidance:
- Use this when the user has a local PDF or remote PDF URL and wants it parsed.
3. **Batch submit URLs**
- Endpoint: `POST /api/tools/papers_submit_urls`
- Body fields:
- `urls: string[] | string` (array or newline-separated string)
- `modelId: string` (optional; applied to all URLs)
- `notifyOnComplete: boolean` (default false)
- `force: boolean` (default false)
- `favoriteFolderId: string | null`
- `favoriteNote: string`
- Usage guidance:
- Use when the user provides many paper URLs and wants them parsed, saved, or both in batch.
### 3.4 Reading and analysis: markdown analysis / raw markdown / PDF link
1. **Get markdown-formatted paper analysis**
- Endpoint: `POST /api/tools/paper_analysis_markdown`
- Body fields:
- `paperId: string` (required)
- `language: "auto" | "zh" | "en" | "both"` (default `"auto"`)
- `scope: "public" | "me" | "auto"` (default `"public"`)
- Usage guidance:
- Use when the user wants **structured, readable analysis** (summary, structure, key points).
- Set `language` according to the user’s preference:
- For Chinese users, prefer `"zh"` or `"both"`;
- If unsure, use `"auto"`.
2. **Get the raw markdown source for a paper**
- Endpoint: `POST /api/tools/paper_markdown_raw`
- Body fields:
- `paperId: string` (required)
- `maxChars: integer (500–120000)` (optional; truncation)
- Usage guidance:
- Prefer this when the user wants to do custom processing, re-summarization, or extraction of formulas/tables.
- For very long papers, set a reasonable `maxChars` and inform the user if the content was truncated.
3. **Get a guarded PDF download link**
- Endpoint: `POST /api/tools/paper_pdf_link`
- Body fields:
- `paperId: string` (required)
- Usage guidance:
- Use when the user wants to download or locally open the PDF.
- Respect copyright and visibility rules; only guide the user to links the API has authorized.
---
### 3.5 Favorite folders and favorite papers
1. **List favorite folders**
- Endpoint: `POST /api/tools/paper_favorite_folders`
- Body: `{}`
- Purpose:
- Get folder IDs, parent/child relationships, and paths to help the user organize and target save locations.
2. **List favorite papers**
- Endpoint: `POST /api/tools/paper_favorites_list`
- Body fields:
- `page, pageSize` (pagination; 1–50)
- `folderId: string | null` (`null` for root; omit for all folders)
- `includeDescendants: boolean` (default false)
- `search: string` (search in notes and titles)
- Purpose:
- Browse the user’s personal library or filter by notes and titles.
3. **Save or update a favorite entry**
- Endpoint: `POST /api/tools/paper_favorite_save`
- Body fields:
- `paperId: string` (required)
- `folderId: string | null` (target folder; `null` for root; omit to reuse existing folder if present)
- `note: string` (optional note)
- Usage guidance:
- After identifying important papers, suggest saving them to an appropriate folder with a short descriptive note.
---
### 3.6 Analysis models and account usage
1. **List available PDF analysis models**
- Endpoint: `POST /api/tools/paper_analysis_models`
- Body: `{}`
- Purpose:
- Show available models under the current plan (including `consumeUnits` and per-parse extra price) to help choose `modelId`.
- Use when the user is concerned about cost or model quality; list models and give recommendations.
2. **Summarize account quota and points**
- Endpoint: `POST /api/tools/account_usage_summary`
- Body: `{}`
- Purpose:
- Summarize current parse quota and points so the user knows how many more papers can be parsed.
3. **List parse history**
- Endpoint: `POST /api/tools/parse_history_list`
- Body fields:
- `page, pageSize` (1–100)
- `chargeMode: string` (optional, e.g., `FREE` or `BALANCE`)
- Purpose:
- Show parse usage records for the last 30 days (which papers, when parsed, potential charges).
---
## 4. Recommended workflows
### 4.1 From research question to paper recommendations (search workflow)
1. Clarify the user’s research question or topic in natural language.
2. If the description is conceptual or fuzzy:
- First call **vector search** `/api/tools/papers_search_vector` to focus on conceptual relevance.
3. If the user provides concrete keywords or title fragments:
- Use **keyword search** `/api/tools/papers_search_keyword`.
4. Organize results by relevance or recency:
- Present titles, years, and short descriptions of main contributions, plus `paperId` for follow-up.
5. For selected papers:
- Call `/api/tools/paper_analysis_markdown` for detailed analysis; or
- Call `/api/tools/paper_markdown_raw` for fine-grained custom processing.
### 4.2 Submit a new paper and obtain analysis (submission + analysis workflow)
1. When the user provides a URL or PDF:
- URL: use `/api/tools/paper_submit_url`
- Local or remote PDF: use `/api/tools/paper_submit_pdf`
2. If the user specifies a folder or note:
- Include `favoriteFolderId` and `favoriteNote` in the request.
3. Wait for parsing to complete (if the API is asynchronous, rely on history or documented IDs):
- Once a `paperId` is available, call `/api/tools/paper_analysis_markdown`.
4. Summarize the analysis in terms of:
- Core contributions, methods, datasets, conclusions, and how they relate to the user’s research question.
### 4.3 Manage personal literature library (favorites workflow)
1. When the user needs an overview of their favorites structure:
- Call `/api/tools/paper_favorite_folders` to list all folders.
2. To view favorites by folder or search string:
- Call `/api/tools/paper_favorites_list` with appropriate `folderId` and `search`.
3. When important long-term papers are identified:
- Call `/api/tools/paper_favorite_save` to create or update favorite records.
4. In summaries:
- Suggest organizing folders by topic or project to simplify future retrieval.
---
## 5. Practical tips
- **Prefer `/api/tools/*`:**
`/api/mcp/tools/*` endpoints are marked `deprecated` in the OpenAPI spec; avoid relying on them for new integrations.
- **Validate parameters:**
Respect OpenAPI constraints (pagination limits, required fields) to avoid unnecessary retries.
- **Post-process responses:**
After each call, convert raw JSON into user-friendly output:
- Concise paper lists (title + year + short description);
- Clear bullet-point summaries (methods, results, limitations);
- Direct conclusions and recommendations relevant to the user’s question (not just raw data dumps).
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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。