{"slug":"jaccen-3dgs-experiment-planner","name":"3dgs-experiment-planner","description":"Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择.","long_description":"---\r\nname: 3dgs-experiment-planner\r\ndescription: \"Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择.\"\r\nlicense: Apache-2.0\r\nuser-invocable: true\r\nmetadata:\r\n  version: \"1.7.0\"\r\n  name_cn: \"3DGS实验设计规划器\"\r\n  description_cn: \"为3DGS研究论文设计严谨的实验方案。推荐数据集、基线方法、评估指标和消融实验矩阵。目标期刊CVPR/ICCV/ECCV/SIGGRAPH/TVCG。适用场景：3DGS论文实验设计、数据集/基线/指标选择、消融实验规划、回应审稿人实验问题。\"\r\n  author: jaccen\r\n  tags: [\"3dgs\", \"gaussian-splatting\", \"experiment-design\", \"research\", \"ablation\", \"paper-writing\"]\r\n  when_to_use:\r\n    - \"Design experiments for a 3DGS research paper\"\r\n    - \"Select datasets, baselines, or evaluation metrics\"\r\n    - \"Plan ablation study matrices\"\r\n    - \"Address reviewer concerns on experiment design\"\r\n    - \"Choose appropriate benchmarks for a 3DGS method\"\r\n    - \"3DGS实验设计 / 消融实验 / 基线选择 / 数据集推荐 / 指标选取\"\r\n\r\n---\r\n\r\n# 3DGS Experiment Planner\r\n\r\nYou are an experienced 3DGS researcher who has served on program committees of CVPR, ICCV, ECCV, and SIGGRAPH. Design experiments that will satisfy rigorous reviewers.\r\n\r\n## Capabilities\r\n\r\n- Recommend datasets and baselines based on method characteristics\r\n- Design comprehensive ablation study matrices\r\n- Suggest evaluation metrics and analysis frameworks\r\n- Plan paper figures and visualizations\r\n- Address common reviewer concerns proactively\r\n\r\n## Workflow\r\n\r\n### Step 1: Understand the Method\r\n\r\nBefore designing experiments, extract:\r\n1. **What problem does the method solve?** (Rendering quality / Speed / Memory / Editing / Geometry / ...)\r\n2. **What is the core technical innovation?** (New primitive / New loss / New architecture / New training / ...)\r\n3. **What are the claimed advantages?** (Better quality / Faster / Less memory / More editable / ...)\r\n4. **What are the expected limitations?** (Complex scenes / Real-time / Large-scale / ...)\r\n\r\n### Step 2: Dataset Recommendation\r\n\r\n#### Standard Benchmarks (Should Use)\r\n\r\n| Dataset | Type | Scenes | Resolution | Difficulty |\r\n|---------|------|--------|------------|------------|\r\n| Mip-NeRF 360 | Forward-facing + 360° | 9 (bicycle, garden, stump, bonsai, ...) | 1008×756 | Medium |\r\n| Tanks and Temples | Large outdoor | 5+ | Variable | Medium |\r\n| Deep Blending | Complex indoor | 7 | Variable | Hard |\r\n| DTU | Object-centric | 124+ | 1600×1200 | Medium |\r\n\r\n#### Specialized Benchmarks (Use Based on Method)\r\n\r\n| Method Type | Recommended Dataset | Reason |\r\n|-------------|-------------------|--------|\r\n| High-frequency / Boundary | Synthetic sharp-edge scenes | Best reveals boundary quality |\r\n| Large-scale | Mill 19 / MatrixCity / Block-NeRF | Tests scalability |\r\n| Dynamic scenes | D-NeRF / HyperNeRF / iPhone / NeRF-DS / Google Immersive / HiFi4G / Plenoptic Video / Meet Room / Waymo Dynamic / Motion Blur / ParticleNeRF (see `references/dynamic-datasets.md` for details) | Temporal consistency, topology change, sparse-view generalization, motion blur robustness, high-frequency detail |\r\n| Editing | NeRF-Synthetic / SHARP | Controllability evaluation |\r\n| Material / Relighting | Light Stage / Polyhaven | Material decomposition quality |\r\n| Autonomous Driving | Waymo / nuScenes / KITTI-360 | Real-world driving scenes |\r\n| Human / Avatar | THUman2.0 / ZJU-MoCap / PeopleSnapshot | Human-specific metrics |\r\n| Feed-Forward / Single-pass | RealEstate10K / ACID | Multi-view forward inference |\r\n| Semantic / Segmentation | LERF / SemanticKITTI | 3D semantic field quality |\r\n| Semantic Foam Benchmarks | CVPR'26 Semantic Foam paper | Volumetric Voronoi semantic segmentation |\r\n| SLAM | Replica / TUM-RGBD / ScanNet | Tracking + mapping accuracy |\r\n| SLAM (Dynamic) | Flow4DGS-SLAM benchmarks | Optical flow-guided dynamic SLAM consistency |\r\n| SLAM (Generalizable Dynamic) | GGD-SLAM (ICRA 2026) benchmarks | Generalizable motion model for dynamic SLAM |\r\n| Medical (Volumetric) | GaussianPile (arXiv 2026（venue 待核实）) benchmarks | Focus-aware PSF projection + additive rasterization for CT/ABUS/LSM/MRI; 16-26× compression, 11× faster than NeRF |\r\n| Robustness / Adverse conditions | RealX3D (NTIRE 2026) | Tests reconstruction in adverse environments (low light, fog, sparse views) |\r\n| Reflection / Transparency | 3DReflecNet (CVPR 2026 Best Paper Candidate) | 120K+ synthetic + 1000+ real objects; 48 material combos; 3 failure modes (specular SH oscillation, transparency ordering, featureless init); 5 tasks |\r\n| Physics Interaction | RAF (CVPR 2026 Findings) scenarios | 5 heterogeneous demos: SPH+3DGS, SPH-MPM+soft body, PBD+statue, robot+rigid, rigid+3DGS container; UE5 rendering |\r\n| Active Mapping / Robotics | MAGICIAN benchmarks | Active vision path planning quality |\r\n| CAD / Parametric | BrepGaussian benchmarks | B-rep reconstruction accuracy |\r\n| Simulation & Robotics | Habitat-GS (Habitat-Sim upgrade) | 3DGS-based robot simulation environments, navigation & interaction tasks |\r\n| Embodied AI / Grasping | GaussianGrasper (T-RO'24) / GraspSplats (CoRL'24) benchmarks | Open-vocabulary grasping & zero-shot manipulation success rates |\r\n| Embodied AI / Manipulation | ManiGaussian (ECCV'24) / RoboSplat (RSS'25) benchmarks | Multi-task manipulation & data augmentation success rates |\r\n| Embodied AI / Navigation | VR-Robo (RAL'25) benchmarks | Real-to-Sim-to-Real navigation success rates, terrain-aware locomotion |\r\n| Embodied AI / Spatial Memory | GSMem (arXiv'26) benchmarks | Zero-shot embodied QA and exploration metrics |\r\n| Cross-Domain / Medical | GS-DOT diffuse optical tomography benchmarks | Tests GS in photon diffusion regime (non-VS application) |\r\n| High-Speed Volumetric | Color-Encoded Illumination (CVPR 2026) paper benchmarks | Tests color-coded temporal info for high-speed volumetric reconstruction |\r\n| Sparse-View NVS | HeroGS (CVPR 2026) / Sparse-View 3DGS Wild paper benchmarks | Hierarchical guidance + diffusion-guided sparse-view enhancement |\r\n| Physics Simulation | FieryGS (ICLR 2026) paper benchmarks | Physics-integrated fire synthesis evaluation |\r\n| Medical Bronchoscopy | RESPIRE paper benchmarks | CT-informed dynamic bronchoscopy reconstruction |\r\n| AD Safety Evaluation | 3DGS AD Safety Eval (SafeComp 2026) paper benchmarks | Industrial fidelity evaluation for autonomous driving perception |\r\n| Forensics / Security | Fake3DGS (arXiv 2026（venue 待核实）) paper benchmarks | First benchmark for 3D manipulation detection in neural rendering |\r\n| Real-Time NVS (Multi-Camera) | 3DTV 3-camera setups | Real-time view synthesis at 40 FPS with multi-camera input |\r\n| Outdoor Robust / LiDAR Prior | EnerGS paper benchmarks | Tests energy-based guidance with partial geometric priors |\r\n| Wireless / Cross-Domain | BiSplat-WRF paper benchmarks | Wireless radiance field (non-VS) reconstruction |\r\n| HDR Dynamic Scenes | HDR-GoPro (HDR-NSFF, ICLR 2026) | First real-world HDR dataset for dynamic HDR scenes, alternating-exposure monocular video |\r\n| Nighttime AD / Low-Light | Nighttime nuScenes / Waymo (Nighttime AD GS, ICRA 2026) | Nighttime subsets of standard AD benchmarks for low-light reconstruction evaluation |\r\n| Egocentric Video | EgoExo4D | Paired ego-exo recordings for 3DGS evaluation in first-person views |\r\n| Cross-Domain Reconstruction | BALTIC benchmark | Controlled cross-domain (air/water) 3D reconstruction benchmark |\r\n\r\n### Step 3: Baseline Selection\r\n\r\n#### Baseline Tiers\r\n\r\n**Tier 1 — Must Compare** (Reviewers will ask for these):\r\n- Original 3DGS (Kerbl et al., SIGGRAPH 2023)\r\n- Mip-NeRF 360 (Barron et al., CVPR 2022)\r\n\r\n**Tier 2 — Should Compare** (Strongly recommended):\r\n- 2DGS or Scaffold-GS (depending on method category)\r\n- One NeRF variant (NeRF / Instant-NGP / Mip-NeRF)\r\n- Proxy-GS (if making acceleration claims)\r\n- 2DGS (if making geometry quality claims)\r\n- SparseSplat (if making feed-forward efficiency claims)\r\n- GlobalSplat (if making feed-forward footprint claims)\r\n- ZPressor (if making many-input-view feed-forward scalability claims)\r\n- VolSplat (if making voxel-aligned or multi-view consistency claims)\r\n- PM-Loss (if making feed-forward depth representation or boundary smoothness claims)\r\n\r\n**Tier 3 — Nice to Compare** (If directly related):\r\n- Methods from the same category:\r\n  - **Compression**: LightGS, Compact-3DGS, NanoGS, MesonGS++, GETA-3DGS (joint prune+quantize), VkSplat (cross-vendor training)\r\n  - **Surface geometry**: SuGaR, 2DGS, 2D-SuGaR (depth+normal priors enhanced 2DGS)\r\n  - **Editing**: Instruct-NeRF2NeRF, GOR-IS (intrinsic decomposition editing)\r\n  - **Training optimization**: Scaffold-GS, Structure-Aware Densification (SIGGRAPH 2026, frequency-aware anisotropic splitting), LeGS (RL density control), CAdam (SIGGRAPH 2026, context-adaptive densification for generative distillation)\r\n- Recent SOTA in your specific sub-area\r\n- 3DTV (if making real-time multi-camera NVS claims)\r\n- GS-DOT (if making cross-domain GS application claims)\r\n- BiSplat-WRF (if making wireless/non-VS domain claims)\r\n- Semantic Foam (if making semantic scene decomposition claims)\r\n- EnerGS (if making outdoor robust reconstruction with partial geometric priors claims)\r\n- HeroGS / Sparse-View 3DGS Wild (if making sparse-view NVS claims)\r\n- FieryGS (if making physics simulation or dynamic scene modeling claims)\r\n- D4RT (if making 4D dynamic reconstruction or temporal-consistent rendering claims)\r\n- Color-Encoded Illumination (if making high-speed or temporal reconstruction claims)\r\n- Fake3DGS (if making robustness/security/forensics claims)\r\n- 3DGS AD Safety Eval (if making autonomous driving perception fidelity claims)\r\n- RESPIRE (if making medical dynamic scene reconstruction claims)\r\n- GEMM-GS (if making GPU-level acceleration / Tensor Core optimization claims)\r\n- FastGS (CVPR 2026 Highlight): 100-second 3DGS training baseline; multi-view consistency screening; 3.32× Mip-NeRF 360 acceleration, 15.45× Deep Blending; applicable ablation: consistency threshold, pruning ratio\r\n- DiffSoup (if making extreme primitive simplification or triangle soup claims)\r\n- FTSplat (if making feed-forward triangle primitive or alternative-to-GS rendering claims)\r\n- SVGS (if making single-view editing or text-guided 3D manipulation claims)\r\n- GS-Surrogate (if making simulation visualization surrogate or rendering approximation claims)\r\n- Pi-GS (if making reference-free sparse-view novel view synthesis claims)\r\n- DropAnSH-GS (if making sparse-view reconstruction with anchor-guided hashing claims)\r\n- FreeFix (if making diffusion-guided refinement or post-processing enhancement claims)\r\n- Flow4DGS-SLAM (if making dynamic SLAM or temporal consistency claims)\r\n- GGD-SLAM (if making generalizable dynamic SLAM or factor graph optimization claims)\r\n- BA-GS (if making SfM-free or COLMAP-free reconstruction claims)\r\n- GaussianPile (if making volumetric medical GS or CT reconstruction claims)\r\n- CAdam (if making generative distillation or context-adaptive densification claims)\r\n\r\n#### Minimum Baseline Count\r\nFor top-venue submission: **at least 4 baselines** across different categories.\r\n\r\n### Step 4: Evaluation Metrics\r\n\r\n#### Standard Metrics (Always Report)\r\n\r\n| Metric | What It Measures | Tool |\r\n|--------|-----------------|------|\r\n| PSNR (dB) | Pixel-level fidelity | Standard |\r\n| SSIM | Structural similarity | Standard |\r\n| LPIPS | Perceptual similarity | lpips Python package |\r\n\r\n#### Supplementary Metrics (Report When Relevant)\r\n\r\n| Metric | When to Use | Note |\r\n|--------|------------|------|\r\n| FPS | Any real-time claim | Report with GPU spec |\r\n| VRAM (GB) | Memory efficiency claim | Peak during training/inference |\r\n| #Gaussians (M) | Compression/scalability | Model size |\r\n| Model Size (MB) | Compression methods | Storage efficiency |\r\n| FID/KID | Generative methods | Distribution quality |\r\n| Chamfer Distance | Geometry reconstruction | Surface ac","tagline":"Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing re","category":"research","tags":["agent-skill"],"author":"jaccen","verified":false,"attribution":{"status":"registry_indexed","statusLabel":"Registry indexed","shortLabel":"REGISTRY INDEXED","sourceLabel":"github candidate review","sourceDetail":"jaccen/Awesome-Gaussian-Skills","creatorName":"jaccen","creatorUrl":"https://github.com/jaccen","sourceUrl":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","indexedBy":"OpenAgentSkill community index","claimUrl":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner#claim-this-skill","claimCta":"Claim this skill","trustNote":"This listing was indexed from public sources and is not marked official until a maintainer claim is approved.","publicNote":"Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals."},"stats":{"stars":149,"forks":10,"verified_installs":0,"successful_runs":0,"total_outcomes":0,"rating":0,"review_count":0,"quality_score":38.93},"quality":{"score":69,"tier":"promising","label":"Promising","summary":"Useful candidate, but compare it with alternatives before adopting.","signals":[{"label":"GitHub stars","value":"149","tone":"neutral"},{"label":"Freshness","value":"1d ago","tone":"positive"},{"label":"Install ready","value":"Yes","tone":"positive"},{"label":"License","value":"Apache-2.0","tone":"neutral"}],"warnings":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured."]},"trust":{"version":"trust-score-v5","score":68,"base_score":76,"outcome_confidence":0,"tier":"review","label":"Sandbox only","summary":"Useful candidate with missing or mixed trust signals. 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issue activity unavailable in current metadata"],"backward_compatible":{"trust_score_v4":{"version":"trust-score-v4","score":76,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout."}}},"trust_score_v4":{"version":"trust-score-v4","score":76,"tier":"strong","label":"Strong shortlist","summary":"Good trust signals with a few areas worth checking before rollout.","recommendedAction":"Test in a sandbox workflow and compare its install path with close alternatives.","dimensions":[{"id":"github_adoption","label":"GitHub adoption","score":62,"weight":0.13,"status":"info","detail":"149 GitHub stars"},{"id":"repo_activity","label":"Stars/forks activity","score":57,"weight":0.08,"status":"warn","detail":"149 stars, 10 forks; issue activity unavailable in current metadata"},{"id":"maintenance","label":"Recent maintenance","score":100,"weight":0.14,"status":"pass","detail":"1d since push"},{"id":"license","label":"License clarity","score":86,"weight":0.09,"status":"pass","detail":"Apache-2.0"},{"id":"documentation","label":"README/SKILL.md completeness","score":76,"weight":0.14,"status":"info","detail":"Public metadata needs stronger README/SKILL.md context"},{"id":"dependency_risk","label":"Dependency/runtime risk","score":80,"weight":0.12,"status":"info","detail":"external package install surface"},{"id":"installability","label":"Install availability","score":92,"weight":0.1,"status":"pass","detail":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner"},{"id":"install_safety","label":"Install command safety","score":92,"weight":0.1,"status":"pass","detail":"standard package or runtime install path"},{"id":"permission_surface","label":"Permission surface","score":100,"weight":0.07,"status":"pass","detail":"no high-risk permission surface in public metadata"},{"id":"repository","label":"Repository evidence","score":86,"weight":0.04,"status":"pass","detail":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner"},{"id":"review_status","label":"Review status","score":66,"weight":0.05,"status":"info","detail":"AI review data available"},{"id":"agent_outcomes","label":"Agent Proven outcomes","score":54,"weight":0.13,"status":"info","detail":"No agent outcome data yet"}],"checks":[{"status":"info","label":"GitHub adoption","detail":"149 GitHub stars"},{"status":"warn","label":"Stars/forks activity","detail":"149 stars, 10 forks; issue activity unavailable in current metadata"},{"status":"pass","label":"Recent maintenance","detail":"1d since push"},{"status":"pass","label":"License clarity","detail":"Apache-2.0"},{"status":"info","label":"README/SKILL.md completeness","detail":"Public metadata needs stronger README/SKILL.md context"},{"status":"info","label":"Dependency/runtime risk","detail":"external package install surface"},{"status":"pass","label":"Install availability","detail":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner"},{"status":"pass","label":"Install command safety","detail":"standard package or runtime install path"},{"status":"pass","label":"Permission surface","detail":"no high-risk permission surface in public metadata"},{"status":"pass","label":"Repository evidence","detail":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner"},{"status":"info","label":"Review status","detail":"AI review data available"},{"status":"info","label":"Agent Proven outcomes","detail":"No agent outcome data yet"},{"status":"warn","label":"Ownership","detail":"No approved owner claim yet"},{"status":"info","label":"OpenAgentSkill usage","detail":"No local usage activity yet"},{"status":"info","label":"Agent outcomes","detail":"No agent outcome data yet"}],"strengths":["AI review approved","Install path is available","Repository evidence is available","Recently maintained repository","Install command has no obvious high-risk pattern"],"warnings":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"],"evidence":{"stars":"149 GitHub stars","repoActivity":"149 stars, 10 forks","lastPushed":"1d since push","license":"Apache-2.0","repository":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","install":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"installReadiness":{"ready":true,"command":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","policy":"human_review_before_install","label":"Human review before install","notes":["Install path is available","Repository evidence is available","License is declared","No Agent Proven outcome evidence yet","1d since push"]},"agentCompatibility":["Codex","Claude Code","Cursor","OpenAgentSkill CLI"],"riskSummary":{"level":"medium","label":"Review before production","notes":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"]},"outcomeEvidence":{"total":0,"successes":0,"failures":0,"notRelevant":0,"successRate":null,"installAttempts":0,"riskBlocked":0,"setupRequired":0,"installSuccessRate":null,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"recentSuccessRate":null,"recentFailureRate":null,"uniqueAgents":0,"agentProvenScore":0,"agentProvenLabel":"Needs first agent run","lastOutcomeAt":null,"label":"No agent outcome data yet"},"autoInstall":{"allowed":false,"sandboxRequired":true,"policy":"human_review_before_install","reason":"Human review or sandbox validation is required before automatic installation."},"bestFor":["research","agent-skill"],"doNotUseFor":["Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface","Automatic installation in a production workspace"],"knownRisks":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"outcome_stats":null,"safety":{"score":68,"level":"review_before_install","label":"Review before install","safety_tier":{"tier":"reviewed","label":"Reviewed with permission notes","badge":"REVIEWED","summary":"Usable candidate, but the agent should surface permission and audit notes before installation.","recommended_action":"Require human approval before installing into a real workspace.","auto_install_policy":"review","reasons":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","68/100 agent safety score"]},"auto_install_allowed":false,"human_review_required":true,"blocked":false,"audit_risk":"needs_review","permission_hints":[{"id":"network","label":"Network access","reason":"Skill likely fetches remote pages, APIs, repositories, or external services.","severity":"medium"}],"policy_warnings":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured."],"constraints_applied":{"max_risk":"medium","needs_install_command":true,"min_stars":0}},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","badge":"REVIEWED","auto_install_policy":"review","auto_install_allowed":false,"blocked":false,"human_review_required":true,"recommended_action":"Require human approval before installing into a real workspace.","reasons":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","68/100 agent safety score"]},"eval":{"version":"openagentskill-skill-eval-v1","status":"review","score":76,"risk_level":"medium","decision":{"recommendation":"manual_review","reason":"Require human approval before installing into a real workspace.","auto_install_allowed":false,"policy":"review","human_review_required":true},"blockers":[],"warnings":["Trust score: Good trust signals with a few areas worth checking before rollout.","Audit score: Needs review","Agent safety gate: Usable candidate, but the agent should surface permission and audit notes before installation.","README/SKILL.md completeness: Public metadata needs stronger README/SKILL.md context","The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"],"validation_plan":["Inspect repository, README/SKILL.md, license, and recent commits before production use.","Install in an isolated workspace or sandbox with no production secrets available.","Run the smallest representative task and record files touched, commands run, network access, and outputs.","Compare the selected skill against at least one alternative when the eval status is review or failed.","Promote only after the agent reports a successful verification result and unresolved warnings are accepted."],"checks":[{"id":"task_fit","label":"Task fit","status":"pass","score":94,"required_for_auto_install":true,"detail":"Task wording matches this skill metadata.","evidence":["Evaluate 3dgs-experiment-planner before installing it in an agent workflow","research","Research agents workflows; Claude Code teams; builders willing to evaluate younger projects"]},{"id":"install_path","label":"Install path","status":"pass","score":92,"required_for_auto_install":true,"detail":"Install handoff is available.","evidence":["npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner"]},{"id":"install_safety","label":"Install command safety","status":"pass","score":92,"required_for_auto_install":true,"detail":"standard package or runtime install path","evidence":["npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner"]},{"id":"trust_score","label":"Trust score","status":"warn","score":76,"required_for_auto_install":true,"detail":"Good trust signals with a few areas worth checking before rollout.","evidence":["Strong shortlist","149 GitHub stars","Apache-2.0"]},{"id":"audit_score","label":"Audit score","status":"warn","score":80,"required_for_auto_install":true,"detail":"Needs review","evidence":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured."]},{"id":"agent_safety_gate","label":"Agent safety gate","status":"warn","score":68,"required_for_auto_install":true,"detail":"Usable candidate, but the agent should surface permission and audit notes before installation.","evidence":["Require human approval before installing into a real workspace.","The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured."]},{"id":"readme_skillmd_completeness","label":"README/SKILL.md completeness","status":"warn","score":76,"required_for_auto_install":false,"detail":"Public metadata needs stronger README/SKILL.md context","evidence":["Usable metadata, review docs"]},{"id":"license_clarity","label":"License clarity","status":"pass","score":86,"required_for_auto_install":true,"detail":"Apache-2.0","evidence":["Apache-2.0"]},{"id":"recent_maintenance","label":"Recent maintenance","status":"pass","score":100,"required_for_auto_install":false,"detail":"1d since push","evidence":["1d since push"]},{"id":"permission_surface","label":"Permission surface","status":"pass","score":100,"required_for_auto_install":true,"detail":"no high-risk permission surface in public metadata","evidence":["Network access: medium"]},{"id":"alternatives","label":"Alternatives available","status":"info","score":55,"required_for_auto_install":false,"detail":"No close alternatives were found in the current shortlist.","evidence":[]}],"endpoints":{"web":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner/evals","api":"/api/agent/evals?slug=jaccen-3dgs-experiment-planner","text":"/api/agent/evals?slug=jaccen-3dgs-experiment-planner&format=text"}},"agent_readable_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"jaccen-3dgs-experiment-planner","name":"3dgs-experiment-planner","description":"Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择.","category":"research","url":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner","repository":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","github_repo":"jaccen/Awesome-Gaussian-Skills"},"suited_tasks":["Research agents workflows","Claude Code teams","builders willing to evaluate younger projects","Search sources","Extract claims","Synthesize findings","Chunk documents","Create embeddings"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add jaccen-3dgs-experiment-planner"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"3dgs-experiment-planner\" agent skill from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"3dgs-experiment-planner\" as a Claude Code skill from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"3dgs-experiment-planner\" from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/jaccen-3dgs-experiment-planner/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/jaccen-3dgs-experiment-planner"},"trust":{"score":76,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"149 GitHub stars","repoActivity":"149 stars, 10 forks","lastPushed":"1d since push","license":"Apache-2.0","repository":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","install":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["research","agent-skill"],"known_risks":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":80,"risk_level":"needs_review","risk_label":"Needs review","warnings":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"]},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Require human approval before installing into a real workspace."},"quality":{"score":69,"label":"Promising"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"1d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","No OpenAgentSkill engagement data yet","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use 3dgs-experiment-planner in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 76/100 Strong shortlist","Audit: 80/100 Needs review","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"jaccen-3dgs-experiment-planner (3dgs-experiment-planner)","install_command":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","risk_summary":"Needs review; Reviewed with permission notes; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"jaccen-3dgs-experiment-planner","task":"Use 3dgs-experiment-planner in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner","api":"https://www.openagentskill.com/api/agent/skills/jaccen-3dgs-experiment-planner","audit":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=jaccen-3dgs-experiment-planner&task=Use%203dgs-experiment-planner%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%203dgs-experiment-planner%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%203dgs-experiment-planner%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/jaccen-3dgs-experiment-planner/install","manifest":"https://www.openagentskill.com/api/registry/manifest/jaccen-3dgs-experiment-planner"}},"machine_metadata":{"version":"openagentskill-agent-metadata-v2","skill":{"slug":"jaccen-3dgs-experiment-planner","name":"3dgs-experiment-planner","description":"Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择.","category":"research","url":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner","repository":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","github_repo":"jaccen/Awesome-Gaussian-Skills"},"suited_tasks":["Research agents workflows","Claude Code teams","builders willing to evaluate younger projects","Search sources","Extract claims","Synthesize findings","Chunk documents","Create embeddings"],"suited_agents":["Codex","Claude Code","Cursor","OpenAgentSkill CLI","CLI"],"install":{"command":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","ready":true,"targets":[{"id":"openagentskill-cli","label":"CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add jaccen-3dgs-experiment-planner"},{"id":"codex","label":"Codex","kind":"agent-prompt","value":"Install the \"3dgs-experiment-planner\" agent skill from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"claude-code","label":"Claude Code","kind":"agent-prompt","value":"Add \"3dgs-experiment-planner\" as a Claude Code skill from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."},{"id":"cursor","label":"Cursor","kind":"agent-prompt","value":"Turn \"3dgs-experiment-planner\" from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes."}],"handoff_url":"https://www.openagentskill.com/api/skills/jaccen-3dgs-experiment-planner/install","manifest_url":"https://www.openagentskill.com/api/registry/manifest/jaccen-3dgs-experiment-planner"},"trust":{"score":76,"label":"Strong shortlist","version":"trust-score-v4","install_policy":"human_review_before_install","evidence":{"stars":"149 GitHub stars","repoActivity":"149 stars, 10 forks","lastPushed":"1d since push","license":"Apache-2.0","repository":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","install":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","installSafety":"standard package or runtime install path","permissionSurface":"no high-risk permission surface in public metadata","documentation":"Usable metadata, review docs","agentOutcomes":"No agent outcome data yet"},"outcome_evidence":{"total":0,"successes":0,"failures":0,"not_relevant":0,"success_rate":null,"recent_success_rate":null,"recent_failure_rate":null,"install_attempts":0,"install_success_rate":null,"risk_blocked":0,"setup_required":0,"avg_output_quality":null,"production_outcomes":0,"last_outcome_at":null,"label":"No agent outcome data yet"},"auto_install":{"allowed":false,"sandbox_required":true,"reason":"Human review or sandbox validation is required before automatic installation."},"best_for":["research","agent-skill"],"known_risks":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"]},"agent_proven":{"version":"agent-proven-v1","score":0,"tier":"unproven","label":"Needs first agent run","summary":"No agent outcome reports yet. Use Resolve, run one narrow sandbox task, then report the result.","metrics":{"totalOutcomes":0,"successfulOutcomes":0,"failedOutcomes":0,"installAttempts":0,"installSuccessRate":null,"successRate":null,"recentSuccessRate":null,"recentFailureRate":null,"riskBlocked":0,"setupRequired":0,"notRelevant":0,"avgOutputQuality":null,"avgTimeToUsefulMs":null,"productionOutcomes":0,"humanReviewRequired":0,"uniqueAgents":0,"lastOutcomeAt":null},"signals":[],"penalties":["No real agent outcome evidence yet"]},"audit":{"score":80,"risk_level":"needs_review","risk_label":"Needs review","warnings":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"]},"safety_gate":{"tier":"reviewed","label":"Reviewed with permission notes","auto_install_policy":"review","auto_install_allowed":false,"human_review_required":true,"blocked":false,"recommended_action":"Require human approval before installing into a real workspace."},"quality":{"score":69,"label":"Promising"},"supply":{"track":"Research and knowledge work","scenario":"Research agents","maintenance":"1d since push","risk":"Needs review"},"alternative_skills":[],"do_not_use_when":["teams that need a vendor-supported SLA","production agents without a repository review","The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","No OpenAgentSkill engagement data yet","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata","Production credentials, payments, or irreversible account changes without explicit human review","Sensitive private data before reviewing repository code, license, and permission surface"],"agent_contract":{"task_input":"Use 3dgs-experiment-planner in an agent workflow","recommended_action":"Require human approval before installing into a real workspace.","install_policy":"review","minimum_review_before_use":["Trust: 76/100 Strong shortlist","Audit: 80/100 Needs review","Safety: 68/100 Review before install","Review repository, license, install command, and permission surface before production use."],"expected_agent_output":{"selected_skill":"jaccen-3dgs-experiment-planner (3dgs-experiment-planner)","install_command":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","risk_summary":"Needs review; Reviewed with permission notes; Review before production","verification_result":"Report the smallest successful task, files touched, warnings, and any missing setup."}},"outcome_feedback":{"endpoint":"https://www.openagentskill.com/api/agent/outcome","method":"POST","requires_resolve_event_id":true,"event_id_source":"Use install_receipt.outcome_feedback.event_id or feedback.event_id returned by /api/agent/resolve for the current task.","expected_outcomes":["success","failed","not_relevant","blocked_by_risk","setup_required"],"payload_template":{"event_id":"<install_receipt.outcome_feedback.event_id or feedback.event_id from /api/agent/resolve>","skill_slug":"jaccen-3dgs-experiment-planner","task":"Use 3dgs-experiment-planner in an agent workflow","agent":"codex","outcome":"success","install_used":true,"risk_blocked":false,"setup_required":false,"task_success":true,"output_quality":4,"error_type":null,"human_review_required":false,"workspace":"sandbox","time_to_useful_ms":120000,"notes":"Report the smallest successful task, setup friction, files touched, and risk notes."}},"endpoints":{"web":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner","api":"https://www.openagentskill.com/api/agent/skills/jaccen-3dgs-experiment-planner","audit":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner/audit","eval":"https://www.openagentskill.com/api/agent/evals?slug=jaccen-3dgs-experiment-planner&task=Use%203dgs-experiment-planner%20in%20an%20agent%20workflow&max_risk=medium","resolve":"https://www.openagentskill.com/api/agent/resolve?task=Use%203dgs-experiment-planner%20in%20an%20agent%20workflow&agent=codex&max_risk=medium","receipt":"https://www.openagentskill.com/api/agent/receipt?task=Use%203dgs-experiment-planner%20in%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text","install":"https://www.openagentskill.com/api/skills/jaccen-3dgs-experiment-planner/install","manifest":"https://www.openagentskill.com/api/registry/manifest/jaccen-3dgs-experiment-planner"}},"supply_profile":{"track":{"slug":"research","label":"Research and knowledge work","shortLabel":"Research","description":"Deep research, source comparison, literature review, RAG, knowledge search, and reports."},"scenario":{"label":"Research agents","description":"I need my agent to research a topic, compare sources, and produce a concise report.","useCases":[{"slug":"research-agents","title":"Research agents"},{"slug":"rag-knowledge","title":"RAG and knowledge"},{"slug":"browser-automation","title":"Browser automation"}]},"applicableAgents":["Claude Code","CLI","Codex","Cursor"],"install":{"ready":true,"command":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","primaryTarget":"CLI","targetCount":4},"githubQuality":{"stars":149,"starsLabel":"149","forks":10,"license":"Apache-2.0","qualityScore":69,"trustScore":76,"auditScore":80},"maintenance":{"status":"fresh","label":"1d since push","daysSincePush":1,"lastPushedAt":"2026-09-05T12:19:23+00:00"},"risk":{"level":"needs_review","label":"Needs review","requiresReview":true,"notes":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata","Needs review"]},"coverageTags":["Research","Research agents","agent-skill"]},"audit":{"audit_score":80,"risk_level":"needs_review","risk_label":"Needs review","quality_score":69,"trust_score":76,"maintenance_score":100,"security_score":81,"install_score":92,"warnings":["The SKILL.md excerpt is truncated in the review, but the provided portion is clear and well-structured.","Quality score needs review","Stars/forks activity: 149 stars, 10 forks; issue activity unavailable in current metadata"]},"quality_signals":{"model":"v2","star_score":15.23,"usage_score":0,"review_score":5.7,"metadata_score":3,"freshness_score":15},"platforms":["Claude Code"],"use_cases":[{"slug":"research-agents","title":"Research agents","url":"https://www.openagentskill.com/use-cases/research-agents"},{"slug":"rag-knowledge","title":"RAG and knowledge","url":"https://www.openagentskill.com/use-cases/rag-knowledge"},{"slug":"browser-automation","title":"Browser automation","url":"https://www.openagentskill.com/use-cases/browser-automation"},{"slug":"document-processing","title":"Document processing","url":"https://www.openagentskill.com/use-cases/document-processing"}],"stacks":[{"slug":"research-report-agent","title":"Research report agent","url":"https://www.openagentskill.com/collections/research-report-agent"},{"slug":"video-creation-studio","title":"Video creation","url":"https://www.openagentskill.com/collections/video-creation-studio"},{"slug":"browser-qa-agent","title":"Browser QA agent","url":"https://www.openagentskill.com/collections/browser-qa-agent"}],"install":"npx skills add jaccen/Awesome-Gaussian-Skills --skill 3dgs-experiment-planner","install_targets":[{"id":"openagentskill-cli","label":"CLI","title":"OpenAgentSkill CLI","kind":"command","value":"npx --yes https://github.com/Leon-Drq/openagentskill/releases/download/cli-v0.3.0/openagentskill-0.3.0.tgz add jaccen-3dgs-experiment-planner","description":"Resolve policy, run the source installer safely, and report a verified install receipt.","copyLabel":"Copy command"},{"id":"codex","label":"Codex","title":"Codex install prompt","kind":"agent-prompt","value":"Install the \"3dgs-experiment-planner\" agent skill from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner. Read its SKILL.md or equivalent instructions first, install only the files needed for this workspace, and summarize any required setup before using it. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"codex\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Give Codex a repo-aware install prompt when the skill is not available through a local CLI.","copyLabel":"Copy prompt"},{"id":"claude-code","label":"Claude Code","title":"Claude Code skill prompt","kind":"agent-prompt","value":"Add \"3dgs-experiment-planner\" as a Claude Code skill from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner. Inspect the skill instructions, place the reusable skill files in the appropriate local skills location for this project, and report the activation steps. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"claude-code\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this prompt to ask Claude Code to add the skill and explain the local activation steps.","copyLabel":"Copy prompt"},{"id":"cursor","label":"Cursor","title":"Cursor rule prompt","kind":"agent-prompt","value":"Turn \"3dgs-experiment-planner\" from https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner into a reusable Cursor project rule or agent instruction. Preserve the core workflow, adapt paths to this repo, and keep the rule scoped to tasks where it is relevant. Skill purpose: Design rigorous experiments for 3DGS research papers. Recommends datasets, baselines, metrics, ablation matrices. Targets CVPR/ICCV/ECCV/SIGGRAPH/TVCG. Use when: designing experiments for a 3DGS paper, selecting datasets/baselines/metrics, planning ablation studies, addressing reviewer concerns on experiments, 3DGS实验设计/消融实验/基线选择. After the install attempt, report the result to https://www.openagentskill.com/api/agent/outcome with POST JSON {\"event_id\":\"install_<unique-id>\",\"skill_slug\":\"jaccen-3dgs-experiment-planner\",\"task\":\"Install 3dgs-experiment-planner\",\"agent\":\"cursor\",\"outcome\":\"success\",\"install_used\":true}. Replace event_id with a unique value and outcome with success or failed. Report success only after the skill is installed and a minimal verification passes.","description":"Use this when installing as Cursor project rules or reusable agent instructions.","copyLabel":"Copy prompt"}],"repository":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","github_repo":"jaccen/Awesome-Gaussian-Skills","version":"1.0.0","license":"Apache-2.0","urls":{"web":"https://www.openagentskill.com/skills/jaccen-3dgs-experiment-planner","repository":"https://github.com/jaccen/Awesome-Gaussian-Skills/tree/main/skills/3dgs-experiment-planner","api":"/api/agent/skills/jaccen-3dgs-experiment-planner","install_api":"/api/skills/jaccen-3dgs-experiment-planner/install"},"meta":{"created_at":"2026-09-06T14:31:09.191235+00:00","updated_at":"2026-09-06T14:31:09.285183+00:00","agent_friendly":true}}