Evaluate LLM endpoints for speed (TTFT, tok/s), concurrency limits, Anthropic protocol compliance, and quality regression against custom use cases. Use to verify vendor claims, compare models head-to-head, or vet a newly released model before adoption.
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Co-create a personal investment-research LLM Wiki (Andrej Karpathy's pattern) where the user's OWN analysis framework becomes a living CLAUDE.md — by interviewing them, NOT by handing them a template. Use whenever the user wants to build a compounding research knowledge base, 投研第二大脑, 投研知识库, or 个人投研 wiki; instantiate Karpathy's LLM Wiki gist for finance/investing; turn their stock-picking, analyst-tracking, or earnings-watching workflow into a structured markdown vault; or build a wiki tracking companies / industries / macro / analysts over time. Pure markdown + wikilinks, NO RAG / vector DB (Karpathy's core idea — do not over-engineer). Also triggers for ingesting research reports / earnings calls / expert notes into an existing wiki, and for post-earnings prediction→fulfillment reviews. Core value = extracting the user's personal investment preferences into THEIR OWN schema, never imposing a standard one.
daymadeCompare two videos and generate interactive HTML reports with quality metrics (PSNR, SSIM) and frame-by-frame visual comparisons. Use when analyzing compression results, evaluating codec performance, or assessing video quality differences
daymadeGenerate format-controlled research reports with evidence tracking, source governance, and multi-pass synthesis. V6.1 adds: source accessibility (circular verification forbidden, exclusive advantage encouraged). Enterprise Research Mode: six-dimension data collection, SWOT/barrier/risk frameworks, and three-level quality control for company research
daymadeScan and remove sensitive data (secrets, API keys, private domains/IPs, PII) from GitHub repository history. Use this skill whenever the user says scan sensitive data, clean git history, remove secrets from repo, sanitize GitHub history, 清理敏感数据, 历史重写, force push, 泄露, or needs to repair a public repo after accidental secret/private context leakage. Also use before any force push to a public repository to verify visibility, backup, and scan results.
daymadeInvestigate and resolve Cloudflare configuration issues using API-driven evidence gathering. Use when troubleshooting ERR_TOO_MANY_REDIRECTS, SSL errors, DNS issues, or any Cloudflare-related problems
daymade
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npx claudepluginhub p/daymade-llm-eval-harness-llm-eval-harnessBenchmark, evaluate, and optimize skills to ensure reliable performance across all LLMs
fastxyz26 Agent Skills (several with runnable, unit-tested scripts) for building, evaluating, securing, and monitoring reliable LLM & AI-agent apps.
ContextJet-aiConfigures and runs LLM evaluation using Promptfoo framework. Use when setting up prompt testing, creating evaluation configs (promptfooconfig.yaml), writing Python custom assertions, implementing llm-rubric for LLM-as-judge, or managing few-shot examples in prompts. Triggers on keywords like promptfoo, eval, LLM evaluation, prompt testing, or model comparison
daymadeFlagship+ skill pack for OpenRouter - 30 skills for multi-model routing, fallbacks, and LLM gateway mastery
jeremylongshoreAgent Skills for NeMo Evaluator SDK
NVIDIA-NeMoAgent and skill evaluation harness with MLflow integration
opendatahub-io