--- name: literature-extensive-read-c7d12db34df3 description: Rapidly skim and summarize academic papers (default:PDF-to-Markdown full text with `## Page XX` pagination and image references) and output a structured extensive-reading summary in Markdown when you need to quickly understand research questions, methods, key results, conclusions, and decide whether intensive reading is worthwhile. license: MIT author: AIPOCH --- > **Source**: [https://github.com/aipoch/medical-research-skills](https://github.com/aipoch/medical-research-skills) ## When to Use - You have a paper converted from PDF to Markdown and need a fast, structured overview before deciding to read it deeply. - You need to extract the research question, methodology, main findings, and conclusions for literature triage. - You are reviewing many papers and want consistent summaries using a fixed template. - You want a quick interpretation of figures/tables referenced as images in the Markdown (only based on what is explicitly shown/described). - You need to produce a UTF-8 Markdown summary file saved to a standard output directory for later review. ## Key Features - Rapid extensive reading workflow: prioritize title/abstract/conclusion, then scan methods and results. - Structured output using a predefined Markdown template. - Supports PDF-to-Markdown inputs that include `## Page XX` pagination headers. - Allows using embedded image references (e.g., `![page-01](...)`) to briefly describe charts/tables when explicitly interpretable. - Strictly summarizes only explicit content from the provided text (no speculation); missing items are marked as **“Not specified”**. - Standardized output location: saves results to `outputs/` (created if missing). ## Dependencies - `pdf-extract` (version: Not specified) — used only when the input is PDF and must be converted to Markdown first. - `securityclaw` (version: Not specified) — optional security audit report saved alongside outputs. ## Example Usage ### Input Assume you have one of the following: 1) A PDF-to-Markdown file (recommended): - `paper.md` (contains full text, may include `## Page XX` and image references) 2) Only a PDF: - `paper.pdf` (convert it first using `pdf-extract`) ### Steps 1) **(Optional) Convert PDF to Markdown** ```bash pdf-extract paper.pdf > paper.md ``` 2) **Read and summarize using the template** - Read `paper.md`, prioritizing: **Title → Abstract → Conclusion**, then scan **Methods** and **Results**. - Follow requirements and quality checks in: - `references/guide.md` - Fill the output template: - `assets/rapid_summary_template.md` - If any field cannot be found in the text, write: **Not specified**. 3) **Save output** - Save the completed summary as a UTF-8 encoded Markdown file to: - `outputs/rapid_summary.md` 4) **(Optional) Save security audit report** - If generated, save the `securityclaw` report to: - `outputs/` ## Implementation Details - **Input format** - Default input is full-text Markdown converted from PDF. - Pagination headers like `## Page XX` may appear and should be treated as page markers, not section headings. - Image references (e.g., `![page-01](...)`) may be used to support brief figure/table descriptions **only when the content is explicitly interpretable**. - **Reading strategy (algorithm)** 1. Extract bibliographic and high-level intent from **Title/Abstract**. 2. Identify the **research question(s)** and scope. 3. Scan **Methods** to capture: data, experimental setup, models, baselines, evaluation metrics, and key parameters (only if explicitly stated). 4. Scan **Results** to capture the main quantitative/qualitative findings and comparisons. 5. Read **Conclusion/Discussion** to capture claims, limitations, and future work. 6. Produce an **intensive-reading recommendation** based on the paper’s stated contributions, clarity of evidence, and relevance to the user’s goal (when provided). - **Output rules** - Use `assets/rapid_summary_template.md` as the sole structure for the final summary. - If information is missing or unclear in the source text, write **Not specified** (do not infer). - Output must be Markdown (`.md`) and saved in **UTF-8** to avoid encoding issues. - Default output language is Chinese unless the user explicitly requests another language. --- Source attribution: aipoch Original project: https://github.com/aipoch/medical-research-skills License: MIT License information: https://opensource.org/license/mit Original upstream instructions; downloaded from Mega AI Hub. ## Upstream license notice MIT License Copyright (c) 2026 Gabriel Moreira Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # Mega AI Hub resource metadata Creator / publisher: aipoch Original project: https://github.com/aipoch/medical-research-skills Attribution basis: Upstream repository explicitly recorded in package mirror path Fields of work: Data & Analytics, Education & Research Roles: Academic Writer, Data Analyst, Researcher Specialties: Specialty not specified Tools: Pdf Extract Country applicability: Country not specified Classification basis: Source catalog labels Instruction SHA-256: f8461880fb430a6fe655808847fac62c070d5afd22ce8580ee8a2e2750203795