Results for “diagnostics”

Use this skill for crawler behavior, log files, sitemap/indexation analysis, crawl-budget diagnostics. Trigger when the task involves agent profile work related to Crawler Analyst Agent, implementation, audits, debugging, strategy, or validation.

Revenue operations analyst specializing in pipeline health diagnostics, deal velocity analysis, forecast accuracy, and data-driven sales coaching. Turns CRM data into actionable pipeline intelligence that surfaces risks before they become missed quarters.

Provides multi-language code navigation via persistent LSP daemons, supporting definitions, references, hover, symbols, and diagnostics for Python, TypeScript, Rust, Go, and more.

Validates product direction before building, runs product diagnostics, founder reviews, user journey audits, and feature prioritization, producing actionable briefs and recommendations.

Operate and troubleshoot CircleCI using the CircleCI CLI. Use when users ask to authenticate CLI access, inspect pipeline/workflow/job status, validate configuration locally, rerun pipelines/jobs, trigger pipelines, or gather actionable diagnostics from CLI outputs.

Diagnose and fix WhatsApp connectivity issues for OpenClaw agents. Use when: a PA is not responding, WhatsApp shows connected but messages don't arrive, the agent is online but not replying, or troubleshooting a new agent setup.

Debug and troubleshoot Azure production issues using AppLens, Azure Monitor, resource health, and systematic diagnosis flows for services like App Service, Functions, AKS, Container Apps, and Messaging.

结构化业务数据分析：附件读取与口径核验、定向筛选、规则/阈值判定、指标异动归因、漏斗/留存/实验分析、经营复盘及可审计报告。当用户提供 Excel、CSV、PDF、图片或多份业务材料，要求查数、判异常、解释变化、比较方案或形成行动建议时使用。Use for evidence-grounded analysis of structured business data, including filtering, rule checks, reconciliation, diagnostics, experiments, and decision reports.

WelineFramework queue diagnostics and operations guide. Use when working on Weline\Queue, queue CLI commands, queue registration, queue_id/biz_key lookups, w_query('queue', ...) CRUD/stat queries, or failures involving queue:collect, queue:run, QueueInterface, and framework queue rows.

Essential Zephyr RTOS kernel services. Covers thread lifecycle and priority, the logging subsystem for diagnostics, and the interactive shell for real-time hardware inspection and debugging. Trigger when writing application flows, adding logging to modules, or creating interactive CLI commands.

Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics, including VPC Flow Logs, NAT, firewall, threat logs, latency, throughput, and Connectivity Tests.

Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"

Econometrics skill for OLS regression and linear models. Activates when the user asks about: "run OLS", "linear regression", "ordinary least squares", "interpret regression results", "heteroskedasticity", "multicollinearity", "regression assumptions", "robust standard errors", "GLS", "WLS", "fit a regression model", "check regression diagnostics", "OLS假设", "最小二乘法", "线性回归", "回归系数", "残差检验", "异方差", "多重共线性", "普通最小二乘", "稳健标准误", "回归诊断"

Comprehensive results analysis for empirical research: generate publication-quality descriptive statistics and balance tables, interpret regression coefficients with economic magnitude and effect sizes, assess identification assumption diagnostics, and produce structured results memos. Use when asked to create summary statistics, Table 1, balance tests, interpret results, assess economic significance, or write results narratives.

Installs and configures the case.dev CLI for legal AI workflows including document vaults, OCR, transcription, and search. Use when the user mentions "case.dev", "casedev", needs to authenticate with case.dev, run diagnostics, set focus targets, list API routes, track jobs, or make raw API calls. Gateway skill for all case.dev skills.

Azure Cosmos DB SDK best practices for .NET, Java, Python, Spring Boot, and LangChain: singleton client, async APIs, connection modes, retry handling, diagnostics, serialization, emulator configuration, ETags, and framework-specific patterns. USE FOR: CosmosClient singleton, async API, Direct vs Gateway mode, retry 429, preferred regions, excluded regions, availability strategy, circuit breaker, SDK diagnostics, serialization enums, emulator SSL, ETag concurrency, conditional create, patch increment, continuation token, content response, Spring Data Cosmos, Spring Boot versions, Newtonsoft dependency, namespace collision, Python async deps, local dev config, LangChain Cosmos DB saver, LangGraph checkpointer, MCP persistent session, tool content format, tool filtering, LangChain JS vectorstore, chat history, semantic cache. DO NOT USE FOR: data modeling (use cosmosdb-data-modeling), queries (use cosmosdb-query-optimization), partition keys (use cosmosdb-partition-key).

Rapid-iteration parameter tuning, diagnostics, and Custom-HLSL scratch-pad authoring for Niagara systems (VibeUE NiagaraService + NiagaraScratchPadService). System/emitter/parameter CRUD is owned by the engine NiagaraToolsets. Use when the user asks to tune emitter rapid-iteration params, compare/diagnose systems, or build scratch-pad/Custom HLSL modules. For emitter color/module work, load niagara-emitters.

Run condition-based vault health diagnostics. 8 categories — schema compliance, orphan detection, link health, description quality, three-space boundaries, processing throughput, stale notes, MOC coherence. 3 modes — quick (schema+orphans+links), full (all 8), three-space (boundary violations only). Returns actionable FAIL/WARN/PASS report with specific fixes ranked by impact. Triggers on "/health", "check vault health", "maintenance report", "what needs fixing".

Expert knowledge for Azure Portal development including troubleshooting, security, and configuration. Use when managing portal RBAC sharing, Intune/Entra mobile access, dashboard JSON, portal policies, or HAR diagnostics, and other Azure Portal related development tasks. Not for Azure Cloud Shell (use azure-cloud-shell), Azure Resource Manager (use azure-resource-manager), Azure Monitor (use azure-monitor), Azure Security (use azure-security).

Perform a static audit of an AL workspace for Business Central against the project's copilot-instructions.md contract. Reports findings by class (Compliance, Code quality, Test coverage, Permissions) and severity (Blocker, Major, Minor, Nit) with file:line citations. Never modifies code. Never invents rules. Use when asked to audit a workspace, run a compliance check, review before PR, or diagnose contract drift.

AI Agent personality diagnosis and configuration system based on MBTI framework. Use when users want to (1) test/diagnose an Agent's personality type, (2) understand the gap between Agent's actual personality and user's desired personality, (3) generate configuration recommendations to adjust Agent behavior, (4) customize Agent's communication style, proactivity, reasoning approach, or execution patterns. Supports both free tier (quick assessment) and premium tier (full 93-question assessment with detailed diagnostics).

Comprehensive exploratory data analysis with publication-quality descriptive tables, correlation matrices, distribution plots, and assumption testing. Generates a standalone EDA report with Table 1 (gtsummary/great_tables), correlation heatmap, distribution diagnostics, VIF for multicollinearity, and normality/homoscedasticity tests. All figures are APA-formatted and colorblind-safe. Use when the user says "exploratory analysis," "EDA," "descriptive statistics," "explore the data," "Table 1," "correlations," "distributions," or when /data-clean completes successfully. Triggers on "EDA," "descriptive," "Table 1," "explore," "correlations."

Use for writing, reviewing, debugging, or testing Python analysis of Bayesian inference results with ArviZ, including 1.x DataTree groups, legacy InferenceData inputs, xarray dimensions and coordinates, conversion, summaries, R-hat/ESS/MCSE diagnostics, posterior predictive checks, PSIS-LOO, Pareto-k, and model comparison. Trigger on chain/draw shape errors, mislabeled groups, flattened samples, missing log likelihood, or misleading diagnostic claims. Do not use to construct or sample PyMC, NumPyro, or Bambi models, for generic plotting, or for deterministic statistics without Bayesian draws.