codex

aasb-aas-ai-product-evaluation-ops

Editorial "AAS AI Product & Evaluation Ops" bundle for Claude Code from Agentic Awesome Skills.

0 on GitHubby sickn33 and contributorsv19.7.0MITupdated 28 days agoSpecialized Product Plugins

Plugin aasb-aas-ai-product-evaluation-ops in Anubis-studios/White-label. Commands read from the repo's manifest — 26 days ago.

What it installs

Skills (13)

  • ab-test-setup

    Use when designing an A/B or split test: define the hypothesis, control and variants, estimate sample size, verify tracking, and predeclare metrics and stopping rules.

  • advanced-evaluation

    Design LLM-as-judge rubrics, direct scores and pairwise comparisons. Use for judge models, evals, position bias and calibration against human labels.

  • agent-evaluation-reporting

    Use when summarizing agent evaluations where autonomous, assisted, failed, timed-out, or invalid outcomes must remain distinct and comparable.

  • agent-evaluation

    Evaluate agent behavior with versioned cases and explicit verifiers. Use when comparing agent or prompt changes, reproducing failures, or running agent regression tests.

  • ai-wrapper-product

    Expert in building products that wrap AI APIs (OpenAI, Anthropic, etc. ) into focused tools people will pay for. Not just "ChatGPT but different" - products that solve specific problems with AI.

  • analytics-product

    Analytics de produto — PostHog, Mixpanel, eventos, funnels, cohorts, retencao, north star metric, OKRs e dashboards de produto.

  • context-window-management

    Strategies for managing LLM context windows including summarization, trimming, routing, and avoiding context rot

  • hugging-face-evaluation

    Add and manage evaluation results in Hugging Face model cards. Supports extracting eval tables from README content, importing scores from Artificial Analysis API, and running custom model evaluations with vLLM/lighteval. Works with the model-index metadata format.

  • kpi-dashboard-design

    Comprehensive patterns for designing effective Key Performance Indicator (KPI) dashboards that drive business decisions.

  • langfuse

    Expert in Langfuse - the open-source LLM observability platform. Covers tracing, prompt management, evaluation, datasets, and integration with LangChain, LlamaIndex, and OpenAI. Essential for debugging, monitoring, and improving LLM applications in production.

  • llm-app-patterns

    Architecture and integration sketches for LLM applications, with explicit retrieval, tool, privacy and verification boundaries.

  • product-manager

    Senior PM agent with 6 knowledge domains, 30+ frameworks, 12 templates, and 32 SaaS metrics with formulas. Pure Markdown, zero scripts.

  • skill-security-audit

    Audit an Agent Skill, MCP server, connector, or desktop extension before installation by tracing code, dependencies, permissions, credentials, data flow, and irreversible actions.

View source on GitHub

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