Tokisakix

swiftscholar-skill

専門分野v1.0.0
作者:Tokisakix更新日 2026-05-11@clawhub_tokisakix/swiftscholar-skill
学術研究

AlphaMoatによると、2026-09時点でswiftscholar-skillのダウンロード数は1,989、スター数は0で、AIスキル全体5,078件中4,437位、専門分野では465件中387位です。

インストール数
167
ダウンロード数
1989
スター数
-
総合順位
#4,437
全体の上位 88% · 専門分野の上位 84%
プラットフォームインストール数ダウンロード数スター数コメント
ClawHub ↗581989--
SkillHub ↗1671973-—

プラットフォームごとに集計方法と集計時点が異なります。

このスキルでできること

キーワード検索や意味検索、PDF・URL の解析依頼、分析結果の取得、お気に入りや利用状況の確認を支援します。API キーが必要です。アップロードによって非公開の研究資料がサービスに送信される場合があり、解析依頼やお気に入り保存で利用枠を消費したりライブラリが変更されたりする可能性があるため、実行前に確認してください。 /api/tools/* を優先し、必須引数を確認して API エラーを報告します。解析完了を確認してから結果を取得してください。

資料公開日 2026-10-27

できること

  • テーマやキーワードで学術論文を検索する
  • 承認された PDF または論文 URL の解析を依頼する
  • 分析結果、お気に入り、利用状況を確認する

使う場面

  • SwiftScholar API で学術論文を検索・管理したい場合
  • 非公開の論文、URL、メモを送る前に承認を得る。解析依頼、お気に入り保存、利用枠を消費する可能性のある操作は事前に確認する

プロンプト例

スキルのドキュメントをもとに生成した例であり、実際の実行結果ではありません。

公開されている研究テーマを SwiftScholar で検索し、送信する検索語を先に提示してください。確認なしにファイルをアップロードしたり、お気に入りを保存したり、利用枠を消費する操作を行ったりしないでください。

月次の推移

ダウンロード数1989
1026154320602026-03 · ダウンロード数 10972026-05 · ダウンロード数 14232026-06 · ダウンロード数 15452026-07 · ダウンロード数 17822026-08 · ダウンロード数 18942026-09 · ダウンロード数 198926-0326-09
スター数-
0112026-03 · スター数 -2026-05 · スター数 -2026-06 · スター数 -2026-07 · スター数 -2026-08 · スター数 -2026-09 · スター数 -26-0326-09

2026-09 から集計方法を変更し、同名スキルを作者ごとに分けて集計し、全スキルを対象にしました。破線は変更前の月で、変更後のデータとは直接比較せず、変更をまたぐ増減も計算していません。

月ダウンロード数前月比スター数
2026-091989—-
2026-081894+6.3%-
2026-071782+15.3%-
2026-061545+8.6%-
2026-051423—-
2026-031097—-

SKILL.md 原文

作者が公開した元のファイルをテキストのまま表示しています。AlphaMoat による編集や審査はしていません。リンクはクリックできません。コマンドは内容を確認してから実行してください。取得日 2026-10-23。

13 KB・ClawHub v1.0.0
---
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.

すべて表示(全 313 行)
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).

専門分野の人気スキル

データ月:2026-09 · ダウンロード数、スター数、インストール数は公開スキルレジストリ(ClawHub、SkillHub)から月単位で集計しています。詳しくはデータの方法論をご覧ください。