panlm

@panlm source repo

16 skills
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5 hours ago last updated

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App Service Log Analysis · panlm bundle
Use when the user wants to analyze application and managed service logs during or after a FIS experiment. Triggers on "analyze app logs", "application log analysis", "check application behavior", "分析应用日志", "查看应用表现", "应用日志分析". Supports two modes: real-time monitoring (during experiment) and post-hoc analysis (after experiment). Reads experiment context from aws-fis-experiment-prepare/execute outputs.

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AWS Fis Experiment Execute · panlm bundle
Use when the user wants to run a prepared AWS FIS experiment where the CloudFormation stack has already been deployed. Triggers on "execute FIS experiment", "run FIS experiment", "start chaos experiment", "执行 FIS 实验", "运行混沌实验", "执行故障注入实验", "run the experiment in [directory]", or when the user provides an FIS experiment template ID (e.g. EXT1a2b3c4d5e6f7). Does NOT deploy infrastructure — only checks that it is already deployed.

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AWS Fis Experiment Prepare · panlm bundle
Use when the user wants to prepare, create, or generate an AWS FIS (Fault Injection Service) experiment configuration. Triggers on "prepare FIS experiment", "create FIS experiment for [scenario]", "generate chaos experiment config", "准备 FIS 实验", "生成 [scenario] 混沌实验配置", "create experiment template for AZ power interruption", "set up fault injection test". Covers Scenario Library pre-built scenarios (AZ Power Interruption, AZ Application Slowdown, Cross-AZ Traffic Slowdown, Cross-Region Connectivity), custom single FIS actions (aws:rds:failover-db-cluster, aws:ec2:stop-instances, etc.), and SSM Automation-based fault injection for Amazon MSK (broker reboot) and ElastiCache Redis/Valkey (primary node reboot, replication group failover).

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Instrumenting With Mlflow Tracing · panlm bundle
Instruments Python and TypeScript code with MLflow Tracing for observability. Must be loaded when setting up tracing as part of any workflow including agent evaluation. Triggers on adding tracing, instrumenting agents/LLM apps, getting started with MLflow tracing, tracing specific frameworks (LangGraph, LangChain, OpenAI, DSPy, CrewAI, AutoGen), or when another skill references tracing setup. Examples - "How do I add tracing?", "Instrument my agent", "Trace my LangChain app", "Set up tracing for evaluation"

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Mlflow Onboarding · panlm
Onboards users to MLflow by determining their use case (GenAI agents/apps or traditional ML/deep learning) and guiding them through relevant quickstart tutorials and initial integration. If an experiment ID is available, it should be supplied as input to help determine the use case. Use when the user asks to get started with MLflow, set up tracking, add observability, or integrate MLflow into their project. Triggers on "get started with MLflow", "set up MLflow", "onboard to MLflow", "add MLflow to my project", "how do I use MLflow".

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Scp Paradigm · panlm
Use when analyzing how industry structure drives firm behavior and market performance, assessing market concentration, entry barriers, or competitive dynamics using the Structure-Conduct-Performance framework. Triggers on "SCP", "structure conduct performance", "industry structure analysis", "market concentration", "entry barriers", "competitive behavior", "antitrust analysis", "SCP范式", "结构-行为-绩效", "行业结构分析", "市场集中度", "进入壁垒".

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AI Daily Report · panlm bundle
Use when generating panlm's daily AI work report — the 00:30 cron task that summarizes the previous day's (Asia/Shanghai) agent activity from agentmemory and appends it to the monthly Feishu doc 工作日报-YYYYMM. Triggers on "AI日报", "生成日报", "工作日报", daily report cron.

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Remote Skill Test · panlm bundle
Use when the user wants to test an agent skill on a remote jump host after updating it locally. Triggers on "test skill remotely", "remote test", "远程测试 skill", "到跳板机上测试", "验证 skill 更新效果". Does NOT run the target skill locally — only orchestrates remote execution and report comparison.

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Gartner Hype Cycle · panlm
Use when assessing technology maturity, judging adoption timing, or positioning a technology or market along the hype-to-productivity curve. Triggers on "hype cycle", "technology maturity", "Gartner", "adoption timing", "is this technology mature", "peak of inflated expectations", "trough of disillusionment", "技术成熟度曲线", "技术处于哪个阶段", "判断技术成熟度", "炒作周期", "新兴技术评估".

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AWS Best Practice Research · panlm bundle
Use when researching, compiling, or assessing best practices for any AWS service, building HA/DR/security checklists from official AWS documentation, or checking whether live AWS resources follow official recommendations. Requires aws-knowledge-mcp-server. Triggers on "best practices", "compile checklist", "summarize HA/DR best practices", "what are the best practices for", "find all best practices", "check my cluster", "audit my redis", "assess my redis", "assessment", "是否符合最佳实践", "检查现有资源", "查找最佳实践", "编译检查清单", "总结最佳实践", "帮我查找", "汇总成表", "帮我检查", "审计一下", "评估一下".

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AWS Service Chaos Research · panlm bundle
Use when the user asks about chaos engineering, fault injection, resilience testing, or HA verification for a SPECIFIC AWS service (e.g., RDS, EKS, MSK, ElastiCache, DynamoDB, S3, Lambda, OpenSearch, etc.). Triggers on "chaos testing on [service]", "fault injection for [service]", "how to test HA of [service]", "FIS scenarios/actions for [service]", "[service] failover testing", "[service] resilience testing", "[service] 混沌测试", "[service] 故障注入", "[service] 高可用验证", "对 [service] 做混沌实验", "test my [service]", "verify my [service] is resilient". Use this skill even when the user phrases it casually like "test my RDS" or "how resilient is my MSK cluster".

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Generate Judgements · panlm bundle
Use when creating or updating test judgement definitions (judge_definitions) for an agent skill evaluation YAML config. Analyzes a skill's SKILL.md and reference files to produce fine-grained yes/no judge questions with scope tags. Triggers on "generate judgements", "create judge definitions", "write test config", "add judgements", "生成判定", "创建测试配置", "更新判定", "补充judgement".

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Value Chain Analysis · panlm
Use when analyzing where profit concentrates across an industry or within a firm, decomposing business activities into primary and support functions to find competitive advantage. Triggers on "value chain", "margin analysis by activity", "where is the profit", "which activities create value", "价值链分析", "利润在哪个环节", "哪个环节利润最高", "分析企业价值活动".

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Awesome Skills Deepdive · panlm bundle
Deep dive analysis of the awesome-openclaw-skills repository. Forks and clones the upstream repo, then systematically fetches every skill's SKILL.md source from GitHub, runs a 10-category security audit on each, and generates a Chinese README summary — all organized by category in a dedicated deepdive repo that syncs to GitHub. Dispatches parallel subagents per category for speed. Use when the user wants to: (1) analyze or audit skills from the awesome-openclaw-skills repo, (2) deep dive into a specific category of community skills, (3) fetch and review SKILL.md source for any ClawHub skill, (4) run security checks on community skills, (5) build a Chinese knowledge base of community skills. Triggers on keywords like "awesome skills", "deepdive skills", "audit community skills", "分析社区 skill", "审查 skill 安全性", "awesome openclaw".

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Eks Workload Best Practice Assessment · panlm bundle
Use when assessing or reviewing Kubernetes workloads running on Amazon EKS for best practice compliance, including pod configuration, security posture, observability, networking, storage, image security, and CI/CD practices. Requires kubectl and awscli access to the target cluster. Triggers on "assess my EKS workloads", "check k8s best practices", "assess container workloads", "evaluate pod security", "workload compliance check", "EKS workload assessment", "检查 K8s 工作负载", "评估容器最佳实践", "审计 EKS 应用", "检查 Pod 配置", "容器安全评估", "工作负载合规检查".

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AWS Bestpractice Research · panlm bundle
Research and compile comprehensive best-practice checklists for ANY AWS service by searching official AWS documentation using aws-knowledge-mcp-server. Produces categorized HA/DR/security checklist tables with source annotations and reference links. Optionally audits live AWS resources against the compiled checklist when the user provides credentials, region, or resource identifiers. Use when the user wants to: (1) research/compile/summarize best practices for an AWS service, (2) build a checklist for auditing HA, DR, or security configurations, (3) find what the official AWS documentation says about configuring a service correctly, (4) generate a best-practice reference table they can use to check existing clusters/resources, (5) check whether a live AWS resource (cluster, instance, table, etc.) follows best practices, (6) audit an existing AWS environment against official recommendations. Triggers on keywords like "research best practices", "compile checklist", "summarize HA/DR best practices", "build a che

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16 published skills