Class Balanced Loss Pytorch
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Supply asset profile
Coding and developer agents
Code review, repo analysis, testing, CI, GitHub, DevOps, and developer workflow skills.
Scenario
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Agent fit
Claude Code + CLI + Codex
Codex, Claude Code, Cursor, CLI, or custom agents.
Install
Ready
npx skills add vandit15/Class-balanced-loss-pytorch
Maintenance
stale
2y since push
Risk
Needs review
Repository appears stale
GitHub quality
803
55/100 quality · 75/100 trust
Coverage tags
Review notes
Repository appears stale · Repository looks stale
Agent adoption scorecard
Trust, audit, and install readiness at a glance
These scores combine public repository metadata, OpenAgentSkill review signals, maintenance freshness, and install readiness. They are a shortlist signal, not a replacement for human review.
Quality
PromisingUseful candidate, but compare it with alternatives before adopting.
Trust
Strong shortlistGood trust signals with a few areas worth checking before rollout.
Audit
Needs reviewInstall readiness, security metadata, maintenance, and adoption risk.
Agent safety v2
52/100 · Avoid automatic install
Sparse or mixed signals. Useful for discovery, but not for autonomous installation.
Test manually in an isolated workspace and compare against safer alternatives.
medium
Network access
Skill likely fetches remote pages, APIs, repositories, or external services.
medium
Filesystem access
Skill may read or write project files, documents, generated artifacts, or local workspace state.
- Repository appears stale
Install targets
Install this skill in your agent workflow
Copy the registry command or an agent-specific install prompt for Codex, Claude Code, and Cursor.
OpenAgentSkill CLI
Use the registry command when your workflow supports the OpenAgentSkill installer.
$ npx skills add vandit15/Class-balanced-loss-pytorchAgent resolve plan
Let an agent verify fit before installing.
The Resolve API returns the selected skill, alternatives, safety policy, audit notes, install target, and copy-paste prompt an agent can follow without scraping this page.
Resolve JSON
/api/agent/resolve?task=Use%20Class%20Balanced%20Loss%20Pytorch%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Resolve text
/api/agent/resolve?task=Use%20Class%20Balanced%20Loss%20Pytorch%20for%20an%20agent%20workflow&agent=codex&max_risk=medium&format=text
Install handoff
/api/skills/vandit15-class-balanced-loss-pytorch/install
Agent should check
- Task fit and alternatives from Resolve API.
- Audit score, trust score, and safety policy warnings.
- Install target compatibility for Codex, Claude Code, Cursor, or CLI.
Copy prompt
Task: Use Class Balanced Loss Pytorch in this workspace.
Resolve first: https://www.openagentskill.com/api/agent/resolve?task=Use%20Class%20Balanced%20Loss%20Pytorch%20for%20an%20agent%20workflow&agent=codex&max_risk=medium
Review install handoff: https://www.openagentskill.com/api/skills/vandit15-class-balanced-loss-pytorch/install
Install command: npx skills add vandit15/Class-balanced-loss-pytorch
Before running it, summarize audit warnings, required permissions, and the fallback skill if install is risky.Agent handoff
Give an agent the install path, not another directory page.
Use the public install endpoint to fetch the command, safety checklist, target prompts, and canonical links for this skill.
Install handoff
/api/skills/vandit15-class-balanced-loss-pytorch/install
LLM text format
/api/skills/vandit15-class-balanced-loss-pytorch/install?format=text
Find alternatives
/api/skills/search?q=Class%20Balanced%20Loss%20Pytorch&limit=3
Agent prompt
Use Class Balanced Loss Pytorch for this task. Review https://www.openagentskill.com/api/skills/vandit15-class-balanced-loss-pytorch/install, then install with: npx skills add vandit15/Class-balanced-loss-pytorchRegistry metadata
Agent-readable profile for automatic skill selection.
This page exposes the same decision, trust, audit, use-case, and install signals through the Registry API, so agents can rank this skill without scraping the UI.
Manifest
/api/registry/manifest/vandit15-class-balanced-loss-pytorch
LLM text
/api/registry/manifest/vandit15-class-balanced-loss-pytorch?format=text
Install alias
/api/registry/install/vandit15-class-balanced-loss-pytorch
Recommend
/api/registry/recommend?task=Use%20Class%20Balanced%20Loss%20Pytorch%20in%20an%20agent%20workflow&limit=3
Agent fit
Coding agents
Use-case tags
Platforms
Python, Computer Vision, Claude Code
Audit report
Needs review · 68/100
Review install readiness, maintenance, trust, quality, and metadata warnings before adding this skill to an agent workflow.
Agent decision cockpit
Needs validation for Coding agents
Do a manual repository review before adding this to an agent workflow.
Role in stack
Needs validation
Primary fit
Coding agents
Trust label
Needs manual review
Install path
Command ready
Use when
- Coding agents workflows
- Claude Code teams
- teams that value GitHub adoption signals
Evidence
- 803 GitHub stars
- install command or GitHub repo available
- 55/100 quality profile
Review first
- Repository looks stale
- No OpenAgentSkill engagement data yet
Implementation path
- 1Install it in a sandbox agent and run one Coding agents task end to end.
- 2Compare output quality, latency, and failure behavior against at least one alternative.
- 3Promote it into production only after reviewing repository permissions, license, and maintenance signals.
Trust profile
Strong shortlist
Good trust signals with a few areas worth checking before rollout.
GitHub adoption
INFO803 GitHub stars
Recent maintenance
FIX2y since push
License clarity
PASSMIT
README/SKILL.md completeness
PASSMetadata includes enough usage and workflow context
Good signals
- AI review approved
- Install path is available
- Repository evidence is available
- Meaningful GitHub adoption signal
Review before install
- Repository looks stale
- Quality score needs review
- Recent maintenance: 2y since push
Recommended action
Test in a sandbox workflow and compare its install path with close alternatives.
Quality profile
Promising candidate for agent workflows
Useful candidate, but compare it with alternatives before adopting.
Workflow fit
Use this skill in these scenarios
Build and ship code
Coding agents
I need a coding agent that can understand a repository, edit code, and review pull requests.
Search private knowledge
RAG and knowledge
I need my agent to build a RAG workflow over documents and retrieve reliable context.
Automate repeated work
Workflow automation
I need my agent to automate a repeated workflow across tools and files.
Stack fit
Add it to a complete workflow
Turn skills into distribution
Content growth agent
A stack for turning newly indexed skills into SEO briefs, social drafts, comparison pages, and reusable publishing workflows.
Inspect, patch, and verify code
Coding review agent
A stack for software agents that inspect repositories, review pull requests, generate tests, and turn findings into shippable patches.
Ingest, retrieve, and cite
RAG knowledge base
A stack for document-heavy agents that ingest files, create searchable knowledge, retrieve relevant context, and answer with grounded sources.
Alternative shortlist
Compare before you install
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Overview
Pytorch implementation of the paper "Class-Balanced Loss Based on Effective Number of Samples"
Imported by the skill-only GitHub discovery pipeline because it matches agent skill, automation, domain workflow, RAG, document-processing, data, finance, security, or developer-tool signals. Protocol-server projects are excluded from automated imports.
Platform Compatibility
Technical Details
- Version
- 1.0.0
- License
- MIT
- Last Updated
- 6/16/2026
- Published
- 6/16/2026
Frameworks & Tools
Decision snapshot
Needs validation
803 GitHub stars
Audit Snapshot
Install and adoption review
- Security
- 97/100
- Maintenance
- 20/100
- Install
- 92/100
Growth loop
Share this skill
Scenario-led draft for Class Balanced Loss Pytorch, with the OpenAgentSkill Update theme and canonical URL.
OpenAgentSkill Update Today: Class Balanced Loss Pytorch Use it when you want your coding agent to carry more repo context and ship repet... 803 stars - robotics-iot Link: https://www.openagentskill.com/skills/vandit15-class-balanced-loss-pytorch?ref=x #AIAgents #OpenAgentSkill
Optional reply with install command
Link for Class Balanced Loss Pytorch: https://www.openagentskill.com/skills/vandit15-class-balanced-loss-pytorch?ref=x Install: npx skills add vandit15/Class-balanced-loss-pytorch
Listing source
Community indexed
This listing was indexed from public sources and is not marked official until a maintainer claim is approved.
- Creator
- vandit15
- Indexed by
- OpenAgentSkill community index
Attribution links to the public repository or creator profile. Creators can claim the listing to update ownership signals.
Claim this skillOwner claim
Claim this skill listing
This community indexed listing is attributed to vandit15 but is not marked official yet. Claim it to add a verified owner signal and make future launch, install, and audit updates easier to trust.
README badge
Add this badge to your GitHub README to show the listing, trust score, and install handoff.
[](https://www.openagentskill.com/skills/vandit15-class-balanced-loss-pytorch)Author
vandit15
@vandit15
Platform Fit
Health Signals
- GitHub stars
- 803
- Quality score
- 39/100
- Last GitHub push
- Feb 18, 2024
- Framework hints
- 2
- OpenAgentSkill views
- 0
- Install copies
- 0
- Outbound clicks
- 0
Community Signal
Share whether this skill looks useful for your agent workflow. Aggregated feedback improves rankings over time.
Trust & Safety
Strong shortlist
- GitHub adoption803 GitHub starsINFO
- Recent maintenance2y since pushFIX
- License clarityMITPASS
- README/SKILL.md completenessMetadata includes enough usage and workflow contextPASS
- Dependency riskno major dependency risk hints in public metadataPASS
- Install availabilitynpx skills add vandit15/Class-balanced-loss-pytorchPASS
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