Results for “acr”

Evaluates open-ended generation quality of multilingual LLMs across brainstorming, planning, and long-form tasks, using AYA and DOLLY datasets with qualitative fluency and quality scoring.

Evaluates social bias in question-answering models using the BBQ benchmark, measuring accuracy and a bias score across ambiguous and disambiguated contexts to reveal reliance on stereotypes.

Persistent per-project memory for Claude Code. Auto-loads project context on session start, tracks sessions with git activity, and writes to native memory. Commands run deterministic Node.js scripts — behavior is consistent across model versions.

Sync Claude Code AI tooling (skills, MCP servers, rules) across Warp, Cursor, and VSCode. Idempotent — safe to re-run. Use when onboarding a new editor, after adding MCP servers, or when standards files change.

Compares two or more band-tagged frameworks and produces a framework-neutral topic matrix showing coverage and gaps across all inputs, plus an optional reference-centric PLC crosswalk document when a reference framework is supplied.

Persistent per-project memory for Claude Code. Auto-loads project context on session start, tracks sessions with git activity, and writes to native memory. Commands run deterministic Node.js scripts — behavior is consistent across model versions.

Manage Heroku config vars safely across environments. Use when the agent needs to inspect, compare, set, remove, or audit Heroku config vars, check `.env` parity, or reason about runtime versus build-time configuration on Heroku.

Implements a continual learning loop for AI coding agents using hooks, two-tier memory (global and local), and automatic pattern detection to persist and apply learnings across sessions.

Enables compact, machine-native agent-to-agent messaging using a shared vocabulary of 340+ 2-character atoms across 7 domains, achieving 3x compression over natural language.

Reconciles project documentation, agent memory, and rule files against the actual codebase after a development session, ensuring accuracy and consistency across all knowledge layers.

Provides a standardized interface for ingesting raw data across domains such as genomics, network analysis, document review, and spatial mapping, converting it into semantic vectors for agent use.

Orchestrates parallel AI agent sessions using dmux, a tmux pane manager, with patterns for research, implementation, testing, and code review across multiple harnesses.

Agent profile for design test strategy across unit, integration, contract, E2E, visual, performance, and regression layers. Use when Codex needs a specialist agent perspective for planning, implementation, review, debugging, validation, or handoff in this domain.

Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.

Build comprehensive AI-native brand asset systems that maintain consistency across all AI-generated content. Train AI tools on brand guidelines, create reusable prompt libraries, and manage visual/voice assets at scale. Use when ", " mentioned.

Deploys and configures CrowdStrike Falcon EDR sensors across Windows, macOS, and Linux endpoints, sets prevention and response policies, validates deployment, and integrates with SIEM platforms.

Evaluates LLMs across 100+ benchmarks from 18+ harnesses (MMLU, HumanEval, GSM8K, safety, VLM) with multi-backend execution on local Docker, Slurm HPC, or cloud platforms.

Generate cinematic videos with Seedance 2.0 using director-level prompts, camera grammar, and multi-mode generation across Chinese, Global, and VIP tiers.

Mines SpecStory coding histories from any agent into a persistent corpus, surfaces reproducible workflows with corroborated evidence, and interactively forges chosen ones into skills installed across agent harnesses.

Loads and processes whole-slide pathology images, builds spatial graphs, trains deep learning models, and analyzes multiplexed immunofluorescence data across 160+ slide formats.

Predicts chromatin state across 919 tracks (histone marks, DNase, TF binding) for DNA sequences via the hosted Genomic Intelligence API, producing a report and JSON results.

Generates short AI videos from text or images across Runway, Kling, Sora, Pika, Seedance, Grok Imagine, and Veo, with provider-specific APIs and prompt guidance.

Manage vector database operations across Pinecone, Weaviate, Qdrant, and ChromaDB, including embedding generation, index creation, metadata filtering, hybrid search, and production deployment for RAG and similarity search.

Call 100+ LLMs through a single OpenAI-compatible interface with LiteLLM — use completion/acompletion/embedding with any provider (Anthropic, OpenAI, Google, Groq, Ollama, etc.), run a proxy server for team rate-limiting and cost tracking, load-balance across providers.

Authors or reviews Know/Understand/Do charts for competency-based learning targets across developmental bands. Handles seven input types from raw curriculum documents to existing LT sets. Routes to upstream skills when stronger inputs are available.

Retrieve interpreted crypto wallet data including portfolio values, token positions, DeFi positions, NFT holdings, transaction history, PnL, token prices, charts, gas prices, swap quotes, and DApp information across 41+ blockchains.

Query blockchain data (balances, token prices, NFT ownership, transfer history, transaction simulation, gas estimates) across Ethereum, Base, Arbitrum, BNB, Polygon, Solana, and more via Alchemy's API, x402, or MPP protocols.

Assess and implement the CISA Zero Trust Maturity Model v2.0 across identity, devices, networks, applications, and data pillars to achieve progressive zero trust maturity.

Runs a broad SEO audit across technical SEO, on-page SEO, schema, sitemaps, content quality, AI search readiness, and GEO, orchestrating specialized sub-skills and subagents.

Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.

Drive a planned change to 100% coverage across an entire codebase when a prior agent run stopped early. Use whenever a refactor, migration, rename, rule-application, or sweeping edit was planned and partially executed but left incomplete — i.e.

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.

Multi-agent orchestration using dmux (tmux pane manager for AI agents). Patterns for parallel agent workflows across Claude Code, Codex, OpenCode, and other harnesses. Use when running multiple agent sessions in parallel or coordinating multi-agent development workflows.

Use before delivering any work product to validate quality. This skill provides a standardized checklist that every agent must complete before marking work as done, ensuring consistent quality across all deliverables regardless of agent or company.

Evaluates LLMs across 60+ academic benchmarks (MMLU, HumanEval, GSM8K, TruthfulQA, HellaSwag). Use when benchmarking model quality, comparing models, reporting academic results, or tracking training progress. Industry standard used by EleutherAI, HuggingFace, and major labs. Supports HuggingFace, vLLM, APIs.