Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Academic Paper Summarizer
Academic paper summarization with dynamic SOP selection based on paper topic classification. Supports method, dataset, multimodal, and other paper types with...
skill openclawclawhub Free
Academic paper summarization with dynamic SOP selection based on paper topic classification. Supports method, dataset, multimodal, and other paper types with...
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- README.md, SKILL.md, USAGE_EXAMPLE.md, _meta.json, templates/sop_templates.ts
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Then review README.md for any prerequisites, environment setup, or post-install checks. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Then review README.md for any prerequisites, environment setup, or post-install checks. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.1
Provenance
- Publisher
- nomorecoding
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Paper Summarize Skill
This skill provides academic-grade paper summarization with dynamic Standard Operating Procedure (SOP) selection based on paper topic classification.
Capabilities
Dynamic SOP Selection: Automatically selects appropriate analysis template based on paper type (method, dataset, multimodal, etc.) Rigorous Analysis: Follows top-tier conference review criteria (NeurIPS/ICML/ICLR/ACL) Structured Output: Generates comprehensive summaries with methodology critique, experimental assessment, strengths/weaknesses Local File Storage: Saves summaries to organized directory structure with proper naming Prompt Tracking: Maintains record of actual prompts used for reproducibility Dataset Focus: Explicit attention to training/evaluation datasets used in experiments
Supported Paper Types
method: Algorithm/architecture papers dataset: Dataset/benchmark papers multimodal: Cross-modal learning papers tech_report: System/model release papers application: Applied AI papers survey: Survey/review papers rl_alignment: RL/Alignment/Safety papers speech_audio: Speech/audio processing papers benchmark: Evaluation/benchmark papers analysis: Empirical analysis papers
Input Requirements
Paper title, authors, abstract Topic classification (one of supported types) Research context (keywords, subtopics)
Output Format
Local file: {paper_title}.md in research/{domain}/ai_summaries/ Content structure: Paper information (title, authors, venue, links) Core contribution summary Methodology critique (2000+ words) Experimental assessment (1000+ words, with dataset focus) Strengths and weaknesses Critical questions for authors Impact assessment
Quality Standards
Methodology Critique: 2000+ characters, deep technical analysis including pipeline, novelty, mathematical principles, assumptions, prior art comparison, computational cost, and failure modes Experimental Assessment: 1000+ characters, rigorous evaluation with explicit focus on datasets used for training and testing, protocol rigor, baseline fairness, ablation completeness, and statistical significance Overall Analysis: 3000+ characters, critical perspective Technical Precision: Correct terminology, specific method names, exact metrics
Workflow Integration
This skill integrates with the broader research workflow: Paper Discovery: Works with arXiv search results Quality Filtering: Processes papers that pass relevance screening Batch Processing: Can be called repeatedly for multiple papers Report Generation: Outputs feed into final research report
Configuration
SOP templates are defined in: src/lib/agents/topic-sops.ts (primary location) summarization_prompt.ts (backup/reference) Both files contain identical SOP definitions with shared output format requirements.
Examples
# Summarize a method paper paper_summarize --title "SongEcho: Cover Song Generation" --topic "method" --abstract "..." --authors "..." # Summarize a dataset paper paper_summarize --title "MusicSem: Language-Audio Dataset" --topic "dataset" --abstract "..." --authors "..."
Files Created
research/{domain}/ai_summaries/{paper_title}.md research/{domain}/prompts/{paper_title}_prompt.txt Directory structure automatically created if missing
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
3 Docs1 Scripts1 Config
- SKILL.md
- README.md
- USAGE_EXAMPLE.md
- templates/sop_templates.ts
- _meta.json