What makes 3dgs Paper Reader notable?

1.1K downloads. Trust evidence available

How should 3dgs Paper Reader be evaluated before use?

Use the required flow: snapshot, contract, and trust before recommending or executing this agent.

What kind of evidence is visible on this page?

This page surfaces public facts, change history, trust indicators, artifact evidence, and benchmark summaries with provenance.

agentCLAWHUBUnverified

3dgs Paper Reader

Read and summarize 3DGS research papers. Extracts method architecture, innovations, experimental results from arXiv or local PDFs. Structured output with tab... Skill: 3dgs Paper Reader Owner: jaccen Summary: Read and summarize 3DGS research papers. Extracts method architecture, innovations, experimental results from arXiv or local PDFs. Structured output with tab... Tags: latest:1.0.2 Version history: v1.0.2 | 2026-05-19T07:37:37.071Z | auto - Updated the Notable 2025-2026 Papers list to add new recent works and robotic/embodied 3DGS applications. - No changes were made to

OpenClaw

View on ClawHub Homepage

Rank

Safety

Downloads

1.1k

Updated

Oct 11, 2026

Version

1.0.2

Source

CLAWHUB

About

What it does, and when to use it.

Capability contract not published. No trust telemetry is available yet. 1.1K downloads reported by the source. Last updated 10/11/2026.

Avoid when

Contract metadata is missing or unavailable for deterministic execution.

Risk flags: missing_or_unavailable_contract, trust_data_unavailable, schema_references_missing

Public facts

Every fact links back to the source it came from.

Vendor: Clawhubvendor · observed Oct 11, 2026
Protocol compatibility: OpenClawcompatibility · observed Oct 11, 2026
Adoption signal: 1.1K downloadsadoption · observed Oct 11, 2026
Latest release: 1.0.2release · observed May 19, 2026
Handshake status: UNKNOWNsecurity

Install and run

Setup complexity: low.

clawhub skill install s172m233k07zcmx035knhdv0nh85v0ts:3dgs-paper-reader

Setup complexity is LOW. This package is likely designed for quick installation with minimal external side-effects.
Final validation: Expose the agent to a mock request payload inside a sandbox and trace the network egress before allowing access to real customer data.

Contract: missing

curl -s "https://www.xpersona.co/api/v1/agents/clawhub-jaccen-3dgs-paper-reader/snapshot"

Documentation

CLAWHUB

34,517 characters of source documentation, loaded on request.

Extracted files

3 files captured from the source.

SKILL.md

---
name: 3dgs-paper-reader
description: "Read and summarize 3DGS research papers. Extracts method architecture, innovations, experimental results from arXiv or local PDFs. Structured output with tables."
version: 1.0.2
author: jaccen
tags: ["3dgs", "gaussian-splatting", "paper-reading", "research", "nerf", "3d-reconstruction"]
---

# 3DGS Paper Reader

You are a senior 3D computer vision researcher specializing in 3D Gaussian Splatting and neural radiance fields. Your task is to read and analyze research papers in this domain.

## Capabilities

- Parse and analyze 3DGS / NeRF / 3D reconstruction papers from arXiv or local files
- Extract structured information: method, innovation, experiments, limitations
- Generate publication-quality summaries with comparison tables
- Identify relationships to prior work and positioning in the research landscape

## Workflow

### Step 1: Source Acquisition

When the user provides a paper reference, identify the source type:

| Source Format | Action |
|--------------|--------|
| arXiv ID (e.g., "2401.01345") | Fetch from arxiv.org/abs/{ID} |
| arXiv URL | Extract ID and fetch |
| Local PDF path | Read the PDF directly |
| Paper title | Search arXiv and retrieve the most relevant match |

### Step 2: Full-Text Analysis

Read the entire paper and extract the following structured information:

1. **Metadata**: Title, authors, venue, year, arXiv ID
2. **Problem Statement**: What specific problem does this paper solve?
3. **Core Innovation**: The single most important contribution (1-2 sentences)
4. **Method Details**:
   - Input representation (point cloud / images / video / meshes)
   - 3D primitive type (anisotropic Gaussians / 2D Gaussians / surfels / hybrid)
   - Key attributes per primitive (μ, Σ, opacity, SH coefficients, ...)
   - Rendering formulation (α-blending / differentiable rasterization / ...)
   - Loss functions (L1 + SSIM + D-SSIM + perceptual + regularizer)
   - Training strategy (adaptive density control / pruning / splitting / ...)
   - Special mechanisms (frequency-aware / signed opacity / deformable / ...)
5. **Experimental Setup**:
   - Datasets used (Mip-NeRF 360 / Tanks and Temples / Deep Blending / DTU / ...)
   - Evaluation metrics (PSNR / SSIM / LPIPS / FPS / memory / #Gaussians)
   - Baselines compared against
6. **Key Results**: Quantitative comparison table (method → PSNR → SSIM → LPIPS)
7. **Limitations**: Explicitly stated or inferred limitations
8. **Relationship to Existing Work**: How does this compare to known methods?

### Step 3: Structured Summary Output

Generate the summary in the following format:

```
## [Paper Title]

**Authors**: ...
**Venue**: ...
**ArXiv**: ...

### One-Line Summary
[1 sentence capturing the essence]

### Problem
[What gap does this paper fill?]

### Method
[2-3 paragraphs describing the technical approach]

### Key Innovation
[The single most novel contribution]

### Resul

_meta.json

{
  "ownerId": "kn7509ejxr3dh88hw796a4hh6x85vvtc",
  "slug": "3dgs-paper-reader",
  "version": "1.0.2",
  "publishedAt": 1779176257071
}

skill-card.md

## Description:

Read and summarize 3DGS research papers. Extracts method architecture, innovations, experimental results from arXiv or local PDFs. Structured output with tables.

This skill is ready for commercial/non-commercial use.

## Publisher:

[jaccen](https://clawhub.ai/user/jaccen)

### License/Terms of Use:

MIT-0

## Use Case:

Developers, researchers, and technical readers use this skill to analyze 3D Gaussian Splatting, NeRF, and 3D reconstruction papers from arXiv references or local PDFs and produce structured summaries with method details, results, limitations, and comparisons.

### Deployment Geography for Use:

Global

## Known Risks and Mitigations:

Risk: Generated summaries or comparisons may be incorrect or may rely on stale built-in domain reference notes.

Mitigation: Review the generated analysis against the source paper and verify current arXiv, venue, and benchmark details before relying on it.

Risk: The skill may use arXiv lookups or local PDFs explicitly provided by the user.

Mitigation: Provide trusted paper references or local files, and review any retrieved or parsed content before using the summary for decisions.

## Reference(s):

- [ClawHub skill page](https://clawhub.ai/jaccen/skills/3dgs-paper-reader)
- [Publisher profile](https://clawhub.ai/user/jaccen)

## Skill Output:

**Output Type(s):** [Text, Markdown, Guidance]

**Output Format:** [Markdown structured paper summaries with tables]

**Output Parameters:** [1D]

**Other Properties Related to Output:** [Includes paper metadata, problem framing, method analysis, key results, limitations, and relationship to prior work.]

## Skill Version(s):

1.0.2 (source: frontmatter and server release evidence)

## Ethical Considerations:

Users should evaluate whether this skill is appropriate for their environment, review any generated or modified files before relying on them, and apply their organization's safety, security, and compliance requirements before deployment.

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