Loading...
Loading...
Found 1,942 Skills
Evaluates agent skills against Anthropic's best practices. Use when asked to review, evaluate, assess, or audit a skill for quality. Analyzes SKILL.md structure, naming conventions, description quality, content organization, and identifies anti-patterns. Produces actionable improvement recommendations.
Graduate a workflow insight from learned/<topic>.md into AGENTS.md as a permanent constraint. Use when a lesson is stable enough to apply to every future session.
Runs a 25-point quality control test on a supplier sample before mass production. Catches the defects that turn into 18% return rates and stranded inventory. Produces a back-message to the supplier with specific fixes required before greenlighting the PO. Use when a user mentions Alibaba sample, supplier sample, sample QC, or before mass production. Trigger phrases: "Amazon supplier sample", "Alibaba sample evaluation", "sample QC", "before mass production", "supplier quality test". Works with zero tools.
Technology stack evaluation and comparison with TCO analysis, security assessment, and ecosystem health scoring. Use when comparing frameworks, evaluating technology stacks, calculating total cost of ownership, assessing migration paths, or analyzing ecosystem viability.
Automated reproduction of comprehensive model evaluation benchmarks following the Benchmark Suite V3. Auto-activates for model benchmarking, comparison evaluation, or performance testing between AI models.
Use when comparing technology stacks, evaluating frameworks/providers, or assessing TCO, security, and ecosystem health for migration decisions.
Organize online information of IPs and conduct multi-dimensional evaluation and scoring. Suitable for assessing the adaptation value of IPs such as novels and scripts, analyzing market potential and innovative attributes
Iterative refinement workflow for polishing code, documentation, or designs through systematic evaluation and improvement cycles. Use when refining drafts into production-grade quality.
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.
Use when "evaluating technology", "choosing frameworks", "stack comparison", "technology decisions", or asking about "React vs Vue", "PostgreSQL vs MySQL", "AWS vs GCP", "build vs buy"
Defines evaluation criteria and scoring methodologies for deliverable assessment
Critically assess external feedback (code reviews, AI reviewers, PR comments) and decide which suggestions to apply using a confidence-based framework with adversarial verification. Use when the user asks to "evaluate findings", "assess review comments", "triage review feedback", "evaluate review output", or "filter false positives".