Data & Analytics

vanterx Bundle

Audits SQL Server Always On Availability Group configuration correctness across all layers — prerequisites, replica design, listener architecture, backup strategy, endpoint security, distributed AG topology, Basic and Contained AG constraints, and application integration readiness. Use this skill when setting up a new AG, reviewing an existing AG design before a DR test, preparing for a failover, or investigating connection failures, listener misconfigurations, backup failures on secondaries, or endpoint certificate expiry. Applies 37 checks (F1–F37) across 7 categories. Trigger for questions about AG prerequisites, session timeout, failure condition level, read-only routing configuration, MultiSubnetFailover, backup preferred replica, distributed AG setup, Basic AG limits, Contained AG, endpoint encryption, or automatic seeding mode during a manual-restore workflow. Companion to /sqlhadr-review (runtime health) and /sqlclusterlog-review (WSFC events).

vanterx Bundle

Batch-analyze a folder of SQL Server .sqlplan files and produce a summary dashboard of the top issues, most common check violations, and deduplicated missing indexes across all plans. Use this skill whenever a user has a folder or collection of .sqlplan files; asks for a workload-level summary across multiple plans; wants to find systemic patterns across a captured workload; or doesn't know which plan to look at first. Trigger after any workload capture that produced multiple .sqlplan files — offer this before individual sqlplan-review calls.

vanterx Bundle

Analyzes SQL Server SPN (Service Principal Name) configuration and Kerberos delegation settings to diagnose authentication failures, NTLM fallback, and double-hop connectivity problems. Use this skill when users receive Kerberos errors, "Cannot generate SSPI context", ANONYMOUS LOGON failures, linked servers fall back to NTLM, AG listener connections fail, or constrained delegation is needed for a middle-tier application, and you need to identify missing, duplicate, or misconfigured SPNs and delegation settings. Applies 54 checks (K1–K54) covering SPN presence, service account binding, AG listener and alias, permissions, Kerberos delegation, AD account sensitivity, Entra ID hybrid, gMSA/FCI scenarios, double-hop platform constraints for linked servers and SSISDB, clock skew and token size prerequisites, SQL Server on Linux keytabs, and client driver limitations.

vanterx Bundle

Analyzes sys.dm_hadr_* DMV output to assess Always On Availability Group replica health, synchronization state, secondary lag, redo and log send queue sizes, and configuration gaps. Use this skill when an availability group is behaving unexpectedly, a secondary replica is lagging, data loss is a concern, a database appears stuck initializing after a failover, or you need a SQL-side snapshot of AG health to complement CLUSTER.LOG and ERRORLOG diagnostics. Applies 27 checks (H1–H28, with H21 retired and merged into sqlag-review F15) covering replica connectivity, data loss risk, recovery time, throughput, configuration, SQL 2016–2022 modern AG features, and seeding/initialization integrity.

vanterx Bundle

Analyze SQL Server execution plans for performance anti-patterns, bottleneck identification, and actionable fix recommendations. Applies 111 checks (S1–S38 statement-level, N1–N73 node-level) covering memory grants, parallelism, cardinality errors, spills, scans, index usage, IQP/PSP features, ADR, CE feedback, hidden UDF cost, and in-plan wait stats. Use this skill whenever a user pastes a .sqlplan file or XML, shares an SSMS execution plan, asks why a query is slow or regressed after a deployment or stats update, mentions a specific operator (Key Lookup, Hash Match, Sort, Nested Loops, Scan), asks about memory grants, spills, compile timeout, parameter sniffing, or plan shape. Also trigger when the user uploads a .sqlplan file, describes a plan tree verbally, or asks for execution plan review, plan analysis, or query tuning help.

vanterx Bundle

Analyze SQL Server wait statistics to identify why the server or a session is slow. Applies 44 checks (V1–V44) covering I/O, locks, parallelism, memory, CPU, TempDB, log I/O, network, latch contention, log space exhaustion, poison/throttle waits, backup I/O, insert hotspots, cumulative skew detection, multi-snapshot trend analysis, In-Memory OLTP, Columnstore, Query Store, Transaction/DTC, Service Broker, Full Text Search, Parallel Redo, forced memory grants, grant timeouts, stolen memory, file I/O latency, SQL 2019/2022 IQP/PSP/ADR feature waits, and TempDB memory-optimized metadata contention. Based on community wait statistics methodology. Use when pasting sys.dm_os_wait_stats or sys.dm_exec_requests output.

vanterx Bundle

Diff two SQL Server execution plans (baseline vs regression) to identify what changed — join strategies, memory grants, operator topology, new warnings, and missing indexes. Applies 20 checks (C1–C20). Use when a query regressed after a deployment, statistics update, schema change, or SQL Server version upgrade.

vanterx Bundle

Parse and analyze SQL Server SET STATISTICS IO, TIME ON output. Extracts per-table IO metrics and per-statement CPU/elapsed times, computes % logical read share, detects 27 performance patterns (I1–I18 IO checks, W1–W9 time checks). Use when a user pastes SSMS statistics output or asks why a query does too much I/O.

vanterx Bundle

Analyze SQL Server trace files and Extended Events output to identify workload-level performance patterns. Applies 25 checks (X1–X12 event-level, X13–X25 workload aggregate) covering long-running queries, high-frequency N+1 patterns, parameter sniffing signals, recompilations, lock timeouts, hash/sort warnings, top resource consumers, and SQL 2019/2022 modern feature events. Use when a user provides Profiler trace output, sys.fn_trace_gettable() results, or Extended Events session data.

vanterx Bundle

Analyze SQL Server execution plans to produce a ranked CREATE INDEX script. Applies 13 checks (D1–D13). Derives index recommendations from operator patterns (Key Lookups, scans, sorts, spools, nested loops, filtered index opportunities, hash match probe-side scans — D1–D10) and the optimizer's explicit MissingIndexGroup suggestions, then validates the generated DDL against engine limits and filtered-index prerequisites (D11–D13). Also accepts sys.dm_db_missing_index_details + sys.dm_db_missing_index_group_stats DMV output directly, without a plan file. Use this skill whenever a user wants index recommendations from an execution plan; asks what indexes would help a query; mentions Key Lookup, index scan, missing index, filtered index, or covering index; or asks to generate CREATE INDEX statements. Trigger after sqlplan-review findings or directly on any .sqlplan file or missing index DMV output.

vanterx Bundle

Analyze SQL Server memory pressure using buffer pool metrics, plan cache composition, memory grants, and memory clerk data. Applies 20 checks (O1–O20) covering Page Life Expectancy degradation, single-use plan cache bloat, RESOURCE_SEMAPHORE queue depth, memory grant timeouts, buffer pool concentration, ColumnStore and In-Memory OLTP footprint, OS memory pressure notifications, and server memory configuration. Use this skill when the server is paging, queries queue for memory grants, or PLE is low and dropping. Trigger when pasting output from sys.dm_os_memory_clerks, sys.dm_os_ring_buffers, sys.dm_exec_query_memory_grants, or PLE perf counters.

vanterx Bundle

SQL Server Database Configuration Review Skill

vanterx Bundle

Analyze SQL Server deadlock XML (from system_health XE session, SSMS deadlock graph, or trace) to identify root cause and produce a prioritized remediation plan. Applies 17 known deadlock patterns (P1–P17). Use when a deadlock monitor captures a graph or users report intermittent deadlock errors (error 1205).

vanterx Bundle

Analyzes SQL Server ERRORLOG files for operational issues, availability group failures, memory pressure, I/O subsystem warnings, and security events. Use this skill whenever a SQL Server instance has experienced unexpected behavior, an AG failover, memory warnings, I/O latency alerts, or abnormal shutdown, and you need a structured timeline of what SQL Server recorded. Applies 33 checks (E1–E33) covering AG health, memory/resource pressure, I/O and storage, startup/shutdown, connectivity, configuration signals, and SQL 2019/2022 modern feature events.

vanterx Bundle

Analyze SQL Server procedure/trigger/function runtime stats collected from sys.dm_exec_procedure_stats into collect.proc_stats. Applies 25 checks (R1–R25) across five categories — top consumers, per-execution efficiency, pattern detection, trend analysis, and advanced runtime patterns. Use when pasting output from the report queries in scripts/collection/04_report_queries.sql.

vanterx Bundle

Analyze SQL Server Reporting Services (SSRS) report server trace logs, RSReportServer.config / ReportingServicesService.exe.config excerpts, ExecutionLog3 query output, and related Windows Event Log entries to diagnose failed report server startups, database connectivity errors, memory pressure and AppDomain recycling, slow or aborted report processing, subscription delivery failures, and scale-out/encryption-key problems. Applies 24 checks (G1–G24) covering trace configuration health, startup and report-server-database connectivity, memory management and recycling, report execution performance from ExecutionLog3, subscription and delivery extensions, and scale-out deployment key management. Use this skill whenever a user pastes ReportServerService_<timestamp>.log content, RSReportServer.config/ReportingServicesService.exe.config XML, ExecutionLog3 output, or describes SSRS symptoms such as "report server unavailable", slow reports, failed subscriptions, or scale-out join errors.

vanterx Bundle

Analyze SQL Server Query Store data to identify regressed queries, plan instability, top resource consumers, query-level wait patterns, configuration issues, and SQL 2019/2022 IQP/PSP/DOP/CE feedback signals. Applies 32 checks (Q1–Q32). Use when a user pastes Query Store DMV output or asks about workload performance trends.

vanterx Bundle

Analyze SQL Server Setup Bootstrap log files to diagnose failed installations, failed Cumulative Update or Service Pack patching, failed cluster node operations, and risky setup-time configuration. Parses Summary.txt, Detail.txt, MSI/MSP logs, ConfigurationFile.ini, and SystemConfigurationCheck_Report content from the Setup Bootstrap Log folder. Applies 24 checks (U1–U24) covering final-result failure and exit-code extraction, failed setup rules (pending reboot, disk space, account permissions, prerequisites, cluster rules), Detail.txt exception forensics, MSI "Return value 3" patterns, and ConfigurationFile.ini review (service accounts, instant file initialization, TempDB layout, mixed authentication, feature sprawl, directory placement). Use this skill whenever SQL Server setup, an in-place upgrade, a patch, or add/remove node fails, or when a user pastes Summary.txt, Detail.txt, or ConfigurationFile.ini content.

vanterx Bundle

Agentic offline orchestrator for end-to-end SQL Server performance reviews. Forms hypotheses from artifacts or symptoms, dispatches the specialised review skills (tsql-review, sqlplan-review, sqlwait-review, sqlstats-review, sqltrace-review, sqlquerystore-review, sqlprocstats-review, sqldeadlock-review, sqlhadr-review, sqlag-review, sqlclusterlog-review, sqlerrorlog-review, sqlspn-review, sqlplan-compare, sqlindex-advisor, sqlplan-batch, sqlmemory-review, sqldiskio-review, sqlencryption-review, sqldbconfig-review, sqlbootstraplog-review, ssrstracelog-review), runs an adversarial check on the primary root cause, and produces a consolidated fix priority with explicit evidence chain, risk, and rollback for each recommendation. Use this skill whenever a user has mixed SQL Server artifacts (.sqlplan, .sql, statistics output, trace data, wait stats, deadlock XML, AG / cluster / ERRORLOG, setspn output, Query Store, procstats, memory clerks, file I/O stats, encryption audit, sp_configure output, setup bootstrap logs

vanterx Bundle

Audits the operational-object migration plan for a SQL Server move with 16 checks (M1-M16) — SQL Agent jobs/operators/alerts/proxies, linked servers, Database Mail, backup devices, custom error messages, server-level triggers, Extended Events sessions, and endpoints. Use this skill when a user is migrating a SQL Server instance and needs to carry over scheduled jobs, linked servers, mail profiles, or other instance-level objects, or asks "what instance objects do I need to recreate after migration." Trigger whenever operational-object portability during a migration is the topic; dispatched here from /sqlmigration-review for the operational-object family.

vanterx Bundle

Audits the security-object migration plan for a SQL Server move with 15 checks (J1-J15) — logins, server and database permissions, credentials, certificates/keys ownership, and Central Management Server registrations. Use this skill when a user is migrating a SQL Server database or instance and needs to carry over logins, permissions, credentials, or certificates, or asks "will my logins still work after migration" or "how do I migrate permissions." Trigger whenever security-object portability during a migration is the topic; dispatched here from /sqlmigration-review for the security-object family.

wpultimatesecurity Bundle

Use when writing any custom database query in WordPress with $wpdb — get_results, get_var, get_row, query, or building WHERE/IN/LIKE/ORDER BY clauses. Uses $wpdb->prepare() with correct placeholders (%d, %s, %f, %i), $wpdb->esc_like() for LIKE, and allowlists for identifiers that cannot be parameterized. Prevents SQL injection. Apply proactively to every query containing a dynamic value.

wpultimatesecurity Bundle

Use when a WordPress plugin or theme stores, processes, or exposes personal data — emails, names, IP addresses, user content, or analytics. Registers data exporters and erasers via wp_privacy_personal_data_exporters / _erasers, declares privacy policy content, anonymizes IPs, and minimizes/secures PII. Helps meet GDPR/CCPA obligations. Apply proactively whenever code touches personally identifiable information.

marve10s Bundle

Use for 'why does X work this way', 'why we picked Y', design rationale, regressions, postmortems, or data-backed thresholds. Discovers available MCPs and queries each evidence category (source control, issue tracker, long-form docs, real-time chat, infrastructure observability, error tracking, product analytics warehouse) in parallel, then returns a cited read on decisions and tradeoffs. Use how for runtime behavior.

programmeranthony Bundle

Use when 用户需要对代码进行安全审计、发现安全漏洞、上线前安全评估、检查代码是否存在安全风险时。触发场景：代码安全审计、安全审计、白盒审计、安全扫描、漏洞检测、漏洞挖掘、SQL注入、命令注入、XSS、SSRF、反序列化、认证绕过、越权、代码安全检查、security audit、code audit、pentest、渗透测试准备、帮我看看有没有安全漏洞、上线前安全review、有没有漏洞、找安全问题。

signalpilot-labs Skill

Load at Step 4 when writing SQL models. Covers column naming, type preservation, JOIN defaults, lookup joins, sibling models, materialization, packages, and filtering rules.

signalpilot-labs Skill

Load when hitting DuckDB syntax errors or writing DuckDB-specific SQL. Covers gotchas that differ from PostgreSQL/MySQL.

signalpilot-labs Skill

SQLite-specific SQL patterns: substr/instr for string ops, || for concatenation, LIKE (no ILIKE), date()/strftime() for dates, CAST for type coercion, no FULL OUTER JOIN, GROUP_CONCAT, typeof(), COALESCE/IFNULL, printf() formatting.

signalpilot-labs Skill

BigQuery-specific SQL patterns: UNNEST for array expansion, STRUCT, ARRAY_AGG, DATE_DIFF/DATE_ADD, backtick-quoted table references, EXCEPT/REPLACE in SELECT, approximate aggregation, partitioned and wildcard tables.

signalpilot-labs Skill

Use this skill before writing any SQL query. Covers: output shape inference (cardinality clues from the question), efficient schema exploration, iterative CTE-based query building, structured verification loop (row count, NULL audit, fan-out check, sample inspection), error recovery protocol, saving output to result.sql and result.csv, turn budget management, and common benchmark traps.

signalpilot-labs Skill

Snowflake-specific SQL patterns: QUALIFY for window filtering, LATERAL FLATTEN for arrays, semi-structured VARIANT data, ILIKE for case-insensitive matching, date functions, and time travel.

axect Bundle

Generate a Python matplotlib plot script following the user's mandatory xkcd style — `with plt.xkcd():` context, `pparam = dict(...)` axis-config, raw-string LaTeX labels, wide canvas (`figsize=(10, 6)`), `dpi=300` savefig. Supports parquet / CSV / NumPy (`.npy`, `.npz`) and four variants: single line, multi-line + legend, scatter / errorbar, multi-panel subplots. Writes the `.py` only — does NOT execute it; the user runs it (typically `uv run`). Use when asked to write an xkcd-style / hand-drawn / sketch-style matplotlib script, plot data in xkcd style from parquet / CSV / `.npy`, scaffold an xkcd line / scatter / errorbar / subplot script, or match the lab's xkcd template. Triggers on: xkcd plot, xkcd matplotlib, xkcd style, hand-drawn / sketch plot, plt.xkcd, comic-style plot; xkcd 플롯, xkcd 그래프, 손그림 그래프, 스케치 스타일 플롯, xkcd 스크립트, xkcd 코드.

axect Bundle

Analyze the HEP-theory postdoc rumor mill (the public Google Sheet at sites.google.com/site/postdocrumor) to see who got offers at which institutions, then pull each offer-holder's publication record from InspireHEP (and OpenAlex + Semantic Scholar for interdisciplinary people) to study what kind of profile lands where. Use when the user wants to study the HEP-theory / cosmology / hep-ph job market from the rumor mill: institute-by- institute cohort profiles (citations, papers, venues, subfield, PhD-age, named fellowships), benchmark their own InspireHEP profile against the accepted cohort, or generate a Korean job-market strategy report. Triggers on: rumor mill, postdoc rumor, HEP rumor mill, hep-th job market, theory postdoc offers, who got offers, offer holders, 루머밀, 포닥 루머, 잡마켓 분석, 오퍼 받은 사람, 합격자 실적 분석, 포닥 전략, InspireHEP 프로필 분석.

axect Bundle

Generate Python matplotlib plotting scripts in the user's scienceplots lab style: with plt.style.context(["science", "nature"]), pparam = dict(...), raw-string LaTeX labels, and fig.savefig(..., dpi=300, bbox_inches='tight'). Support parquet, CSV, NPY/NPZ data and single-line, multi-line, scatter/errorbar, or subplot variants. Generate both the reproducible plotting script and the requested PNG/PDF/SVG figure by default. Use for publication-style plot scripts, science/nature figures, plot-from-data scaffolds, and Korean or English requests for matplotlib graph scripts.

bastidood Bundle

Dialect-aware Drizzle ORM conventions for safe query, mutation, and transaction boundaries. Use when writing or reviewing Drizzle schemas, queries, transactions, or raw SQL.

aizech Bundle

Retrieves and analyzes operational metrics from radiology information systems. Use when user mentions "radiology KPIs", "productivity metrics", "turnaround time analysis", "workload distribution", or needs operational analytics.