2,381 skills found ¡ Page 47 of 80
benchflow-ai / mip-solver-and-solution-auditOperational workflow for hard integer-programming optimization tasks: selecting an installed solver, preserving solver/incumbent certificates, extracting feasible schedules, recomputing metrics from final outputs, and writing consistent reports
benchflow-ai / Automatic Speech Recognition (ASR)Transcribe audio segments to text using Whisper models. Use larger models (small, base, medium, large-v3) for better accuracy, or faster-whisper for optimized performance. Always align transcription timestamps with diarization segments for accurate speaker-labeled subtitles.
benchflow-ai / pdf-editingComplete guide for reading and editing PDF documents with PyMuPDF.
benchflow-ai / jax-skillsHigh-performance numerical computing and machine learning workflows using JAX. Supports array operations, automatic differentiation, JIT compilation, RNN-style scans, map/reduce operations, and gradient computations. Ideal for scientific computing, ML models, and dynamic array transformations.
benchflow-ai / workload-balancingOptimize workload distribution across workers, processes, or nodes for efficient parallel execution
benchflow-ai / pddl-skillsAutomated Planning utilities for loading PDDL domains and problems, generating plans using classical planners, validating plans, and saving plan outputs. Supports standard PDDL parsing, plan synthesis, and correctness verification.
benchflow-ai / rl-post-trainingDiagnostic guide for RL-based post-training of language models (GRPO, PPO, REINFORCE, DPO). Use proactively when debugging a training pipeline that shows no improvement, loss anomalies, reward stagnation, NaN gradients, or other unexpected behavior during reinforcement learning fine-tuning.
benchflow-ai / grpoReference for the GRPO (Group Relative Policy Optimization) algorithm
benchflow-ai / memory-optimizationOptimize Python code for reduced memory usage and improved memory efficiency
benchflow-ai / python-parallelizationTransform sequential Python code into parallel/concurrent implementations
benchflow-ai / hierarchical-taxonomy-clusteringBuild unified multi-level category taxonomy from hierarchical product category paths from any e-commerce companies using embedding-based recursive clustering with intelligent category naming via weighted word frequency analysis.
benchflow-ai / exoplanet-workflowsGeneral workflows and best practices for exoplanet detection and characterization from light curve data
benchflow-ai / react-best-practices**IMPORTANT**: Any change to React or Next.js code must read through this skill first. React and Next.js guidelines from Vercel Engineering covering visual instability, layout shifts, CLS, flickering, hydration issues, and font loading.
benchflow-ai / lean4-theorem-provingUse when working with Lean 4 (.lean files), writing mathematical proofs, seeing "failed to synthesize instance" errors, managing sorry/axiom elimination, or searching mathlib for lemmas - provides build-first workflow, haveI/letI patterns, compiler-guided repair, and LSP integration
a5c-ai / assimilate-popular-workflowsThis skill should be used when the user asks to "find skills in the wild", "assimilate popular workflows", "discover SKILL.md files in repos", "research external skills", "find workflow patterns", "survey the skill landscape", "what skills exist out there", or wants to investigate public repositorieâĻ
a5c-ai / process-builderScaffold new babysitter process definitions following SDK patterns, proper structure, and best practices. Guides the 3-phase workflow from research to implementation.
a5c-ai / frontmatter-parsingYAML frontmatter parsing and manipulation for .planning/ documents. Provides read, write, update, query, and validation operations on frontmatter blocks in GSD markdown artifacts.
a5c-ai / git-integrationGit commit patterns, formats, and conventions for GSD methodology. Provides atomic commits per task, structured commit messages, planning file commits, branch management, and milestone tag operations.
a5c-ai / model-profile-resolutionResolve model profile (quality/balanced/budget) at orchestration start and map agents to specific models. Enables cost/quality tradeoffs by selecting appropriate AI models for each agent role.
a5c-ai / roadmap-managementRoadmap parsing, analysis, and mutation operations for ROADMAP.md. Handles phase and milestone lifecycle including add, insert (decimal), remove, complete, and requirements coverage analysis.
a5c-ai / state-managementSTATE.md reading, writing, and field-level updates. Provides cross-session state persistence via .planning/STATE.md with structured fields for current task, completed phases, blockers, decisions, and quick tasks.
a5c-ai / template-scaffoldingTemplate loading, variable filling, and scaffolding for all GSD artifacts. Manages 22+ templates covering every document type in the GSD system, from PROJECT.md to milestone archives.
a5c-ai / verification-suitePlan structure validation, phase completeness checks, reference integrity verification, and artifact existence confirmation. Provides the structured verification layer ensuring GSD artifacts are well-formed and complete.
a5c-ai / guardrails-ai-setupGuardrails AI validation framework setup for LLM applications. Implement input/output validation, safety checks, and structured output enforcement.
a5c-ai / langgraph-state-graphLangGraph StateGraph builder with state schema design. Create stateful agent workflows with cycles, conditionals, and persistence.
a5c-ai / mcp-app-scaffoldingScaffolds MCP App project structure with correct directory layout, dependencies, entry points, and framework-specific templates. Handles React (useApp hook), Vanilla JS, Vue, Svelte, Preact, and Solid.
a5c-ai / mcp-app-verificationComprehensive verification checklists for MCP Apps. Tests with basic-host reference, validates handler-before-connect, text fallback, resource URI linking, single-file bundling, host styling, CSP, and legacy pattern detection.
a5c-ai / mcp-host-styling-integrationIntegrates MCP App UI with host theming system. Applies host CSS variables, handles onhostcontextchanged, safe area insets, display mode detection, and fullscreen configuration.
a5c-ai / mcp-tool-resource-patternImplements the core MCP Apps architectural pattern where a Tool declares _meta.ui.resourceUri referencing a registered Resource. Covers registerAppTool, registerAppResource, text fallback, structuredContent, and app-only helper tools.
a5c-ai / mem0-integrationMem0 memory layer integration for AI agents. Implement persistent, semantic memory for long-term context retention and personalization.
