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benchflow-ai

benchflow-ai

440 Skills published on GitHub.

transformers

Work with state-of-the-art machine learning models for NLP, computer vision, audio, and multimodal tasks using HuggingFace Transformers. This skill should be used when fine-tuning pre-trained models, performing inference with pipelines, generating text, training sequence models, or working with BERT, GPT, T5, ViT, and other transformer architectures. Covers model loading, tokenization, training with Trainer API, text generation strategies, and task-specific patterns for classification, NER, QA, summarization, translation, and image tasks. (plugin:scientific-packages@claude-scientific-skills)

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grpc-service-development

Build high-performance gRPC services with Protocol Buffers, bidirectional streaming, and microservice communication. Use when building gRPC servers, defining service contracts, or implementing inter-service communication.

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proto-gen

Generate C++ and Python code from Protocol Buffer definitions. Use when user asks to generate proto files, compile protos, regenerate gRPC code, or mentions protobuf/gRPC generation.

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morph-apply

Fast file editing via Morph Apply API (10,500 tokens/sec, 98% accuracy)

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numpy-core

Fundamental NumPy operations including ndarray creation, dtypes, shape manipulation, and basic operations with a focus on memory alignment and data views. Triggers: numpy, ndarray, dtype, reshape, memory alignment, array-creation.

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numpy-linalg

Linear algebra operations in NumPy, including matrix multiplication, SVD, system solving, and least squares fitting. Triggers: linalg, matrix multiplication, SVD, eigenvalues, matrix decomposition, lstsq, multi_dot.

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numpy-ufuncs

Universal functions (ufuncs) for vectorization, including reductions, in-place operations, and custom Python-function wrapping. Triggers: ufunc, vectorize, reduce, accumulate, frompyfunc, in-place.

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cost-latency-optimizer

Reduces LLM costs and improves response times through caching, model selection, batching, and prompt optimization. Provides cost breakdowns, latency hotspots, and configuration recommendations. Use for "cost reduction", "performance optimization", "latency improvement", or "efficiency".

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llm-serving-patterns

LLM inference infrastructure, serving frameworks (vLLM, TGI, TensorRT-LLM), quantization techniques, batching strategies, and streaming response patterns. Use when designing LLM serving infrastructure, optimizing inference latency, or scaling LLM deployments.

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ml-inference-optimization

ML inference latency optimization, model compression, distillation, caching strategies, and edge deployment patterns. Use when optimizing inference performance, reducing model size, or deploying ML at the edge.

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serving-llms-vllm

Serves LLMs with high throughput using vLLM's PagedAttention and continuous batching. Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.

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log-analysis

Log file analysis including reading, searching, filtering, and pattern matching. Use when investigating issues in logs, searching for errors, or analyzing application behavior.

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mailhog

This skill should be used when the user asks to "set up MailHog", "test email functionality", "configure MailHog", "send test emails", "check MailHog messages", "configure SMTP testing", or "manage email capture". Provides comprehensive MailHog email testing server setup and management.

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r-data-science

R programming for data analysis, visualization, and statistical workflows. Use when working with R scripts (.R), Quarto documents (.qmd), RMarkdown (.Rmd), or R projects. Covers tidyverse workflows, ggplot2 visualizations, statistical analysis, epidemiological methods, and reproducible research practices.

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stan-development

Expert guidance for Stan probabilistic programming language development, including modern syntax, cmdstanr/cmdstanpy integration, and testing patterns

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stan-fundamentals

Foundational knowledge for writing Stan 2.37 models including program structure, type system, distributions, and best practices. Use when creating or reviewing Stan models.

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git-advanced

Advanced Git operations and workflows including interactive rebasing, conflict resolution, history manipulation, bisecting for bugs, cherry-picking, reflog recovery, and branch management strategies. Use for: (1) Interactive rebasing and commit cleanup, (2) Complex merge conflict resolution, (3) Git bisect for bug hunting, (4) History rewriting and cleanup, (5) Branch strategy implementation (Git Flow, trunk-based), (6) Recovering lost commits with reflog

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git-mastery-suite

Advanced Git operations including rebasing, conflict resolution, history rewriting, worktrees, bisect, submodules, hooks, and complex workflows. Use for sophisticated Git challenges beyond basic add/commit/push, including fixing repository states, optimizing history, and managing complex branching strategies.

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git

Automate Git workflow for AgentOS. Handles branch creation, TODO-based commits, and PR generation following project conventions.

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repo

Repository information using GitHub CLI. Trigger when user wants to view repository details ("show repo info", "what's this repo about"), list repositories ("list my repos", "show repos for user"), or check repository metadata ("stars", "languages", "topics").

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python-programming

Master Python fundamentals, OOP, data structures, async programming, and production-grade scripting for data engineering

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Legacy Code Reviewer

Expert system for identifying deprecated patterns, suggesting refactoring to modern standards (Python 3.12+, ES2024+), checking test coverage, and leveraging AI-powered tools. Proactively applied when users request refactoring, updates, or analysis of legacy codebases.

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python-analytics

Python data analysis with pandas, numpy, and analytics libraries

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embedding-strategies

Select and optimize embedding models for semantic search and RAG applications. Use when choosing embedding models, implementing chunking strategies, or optimizing embedding quality for specific domains.

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sentence-transformers

Framework for state-of-the-art sentence, text, and image embeddings. Provides 5000+ pre-trained models for semantic similarity, clustering, and retrieval. Supports multilingual, domain-specific, and multimodal models. Use for generating embeddings for RAG, semantic search, or similarity tasks. Best for production embedding generation.

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content-similarity-checker

Compare document similarity using TF-IDF, cosine similarity, and Jaccard index. Use for plagiarism detection, duplicate finding, or content matching.

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google-gemini-embeddings

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semtools

This skill provides semantic search capabilities using embedding-based similarity matching for code and text. Enables meaning-based search beyond keyword matching, with optional document parsing (PDF, DOCX, PPTX) support.

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csv-excel-merger

Merge multiple CSV/Excel files with intelligent column matching, data deduplication, and conflict resolution. Handles different schemas, formats, and combines data sources. Use when users need to merge spreadsheets, combine data exports, or consolidate multiple files into one.

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data-profiler

Profile datasets to understand schema, quality, and characteristics. Use when analyzing data files (CSV, JSON, Parquet), discovering dataset properties, assessing data quality, or when user mentions data profiling, schema detection, data analysis, or quality metrics. Provides basic and intermediate profiling including distributions, uniqueness, and pattern detection.

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log-analyze

Parse and analyze system and application logs. Use when the user says "find errors in logs", "analyze logs", "check journalctl", "what's in the logs", "debug from logs", or asks to investigate log files.

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nginx-configuration

Configure Nginx web server for high-performance reverse proxy, load balancing, SSL/TLS, caching, and API gateway functionality.

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rate-limiting

Implement rate limiting to prevent brute force attacks, spam, and resource abuse. Use this skill when you need to protect endpoints from automated attacks, prevent API abuse, limit request frequency, or control infrastructure costs. Triggers include "rate limiting", "rate limit", "brute force", "prevent spam", "API abuse", "resource exhaustion", "DoS", "withRateLimit", "too many requests", "429 error".

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OpenSSL

Expert guidance for OpenSSL operations including certificate generation, key management, CSR creation, certificate verification, encryption, and PKI operations. Use this when working with SSL/TLS certificates, cryptographic keys, or PKI infrastructure.

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PKI and X.509

Expert guidance for Public Key Infrastructure (PKI) and X.509 certificates including certificate structure, DN parsing, CSR generation, certificate signing, revocation (CRL/OCSP), key management, and OpenSSL commands. Use this when working with digital certificates, certificate authorities, or cryptographic key management.

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scripting

DevOps scripting with Bash, Python, and Go for automation, tooling, and infrastructure management

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latex-build

Builds LaTeX documents using latexmk with live preview and dependency tracking. Use when setting up builds, live preview, or troubleshooting compilation.

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latex-pdf-compiler

Compiles LaTeX source code to PDF using pdflatex. Use this skill whenever the user asks to create and compile LaTeX documents, generate PDFs from LaTeX, or compile existing LaTeX code in artifacts.

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latex-writing

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claude-code-history-files-finder

Finds and recovers content from Claude Code session history files. This skill should be used when searching for deleted files, tracking changes across sessions, analyzing conversation history, or recovering code from previous Claude interactions. Triggers include mentions of "session history", "recover deleted", "find in history", "previous conversation", or ".claude/projects".

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searcher

Use this skill when the user wants to search for files by text content, find files containing specific text, or get a list of file paths related to a search term. The skill searches the codebase and returns matching file paths with context.

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assisting-reverse-engineering

Provides reverse engineering analysis support including function identification, data structure analysis, and behavior understanding. Use when analyzing unknown binaries, understanding program structure, or investigating binary behavior.

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binary-triage

Performs initial binary triage by surveying memory layout, strings, imports/exports, and functions to quickly understand what a binary does and identify suspicious behavior. Use when first examining a binary, when user asks to triage/survey/analyze a program, or wants an overview before deeper reverse engineering.

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forge-lang-python

Python development standards including pytest, ruff, black, and mypy. Use when working with Python files, tests, or dependencies.

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polyglot-integration

Integrate multiple programming languages using FFI, native bindings, gRPC, or language bridges. Use when combining strengths of different languages or integrating legacy systems.

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rust-ffi

Microsoft Pragmatic Rust FFI Guidelines. Use when working with C/C++ interop, creating cdylib, writing unsafe FFI code, or multi-DLL Rust projects.

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rust-language

Guide for writing Rust code covering ownership, borrowing, lifetimes, error handling, async programming, and Rust best practices

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pdb-database

Access RCSB PDB for 3D protein/nucleic acid structures. Search by text/sequence/structure, download coordinates (PDB/mmCIF), retrieve metadata, for structural biology and drug discovery.

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python-project

Use when creating Python projects, managing dependencies with uv, configuring pyproject.toml, building packages, or publishing to PyPI - covers project initialization, dependency management, and distribution; NOT for testing or performance (plugin:python@dot-claude)

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uv

This skill should be used when creating new Python projects or managing Python dependencies. IMPORTANT - uv must ALWAYS be used for any Python-related commands in Python projects (running scripts, installing packages, creating virtual environments, etc.). Never use pip, python directly, or other package managers - always use uv commands (uv run, uv add, uv pip, etc.).

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