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kimtth

@kimtth source repo

139 published skills · page 1 of 2

  1. Caveman Review · kimtth bundle
    Compressed code review - one line per finding with location, problem and fix. Use for /caveman-review, "review this PR", or "review the diff".
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  2. Zen Prompt Measure · kimtth
    Use when optimizing a GitHub Copilot customization artifact with the Zen CLI, running zen optimize/detect/selfcheck, or interpreting a Zen report. Do not use for generic prompt rewriting, hooks, mcp.json, or automatic candidate application.
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  3. Azure Ml LLM Trainer · kimtth bundle
    Train or fine-tune LLMs on Azure ML managed compute with TRL trainers. Uses direct trainer loops (SFT, DPO, RL) without relying on serverless APIs or Hugging Face infrastructure.
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  4. Azure Ml Dataset Creator · kimtth bundle
    Generate synthetic and simulated datasets for evaluation and fine-tuning using Azure AI Foundry simulators. Create non-adversarial task data, adversarial safety data, and conversation datasets without manual data collection.
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  5. Azure Ml Model Evaluation · kimtth bundle
    Evaluate generative AI applications and models locally or in the cloud using Azure AI Evaluation SDK. Measure quality, safety, and performance with built-in and custom evaluators.
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  6. Fabric Core · kimtth
    Core Microsoft Fabric platform reference: topology, authentication, token scopes, REST API base URL, pagination, long-running operations, throttling, workspace and item resolution, OneLake access, and common gotchas. Use this skill whenever working with Fabric REST APIs, managing workspaces/items, or troubleshooting auth errors.
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  7. Check Updates · kimtth
    Check for skills-for-fabric marketplace updates at session start. Compares local version against GitHub releases and shows changelog if updates are available. Use when the user wants to: (1) check for skill updates, (2) see what's new in skills-for-fabric, (3) verify current version. Triggers: "check for updates", "am I up to date", "what version", "update skills", "show changelog".
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  8. Fabric Alm Cicd · kimtth
    Plan, implement, review, and troubleshoot Microsoft Fabric ALM and CI/CD workflows using Git integration, deployment pipelines, Variable Libraries, Fabric REST APIs, fabric-cicd, GitHub Actions, or Azure DevOps. Use when the user asks about source control, deploy, promote, release, dev/test/prod, environment variables, deployment pipeline automation, Git sync, fabric-cicd, or Fabric item definition validation.
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  9. Fabric Lakehouse · kimtth
    Fabric Lakehouse design, schemas, shortcuts, security, optimization, and PySpark patterns. Use when designing Lakehouse solutions, managing Delta tables, configuring OneLake shortcuts, or writing PySpark/Spark SQL code for Fabric notebooks.
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  10. Fabric Data Agent · kimtth
    Design, configure, evaluate, and govern Microsoft Fabric Data Agents for natural-language Q&A over Lakehouse, Warehouse, Power BI semantic model, KQL database, mirrored database, ontology, or Microsoft Graph data. Use when the user asks for Fabric data agent, conversational analytics, NL2SQL, NL2DAX, NL2KQL, data-agent instructions, example queries, agent evaluation, publishing, sharing, governance, diagnostics, or ALM.
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  11. Synapse Migration · kimtth bundle
    Port Azure Synapse Analytics notebooks, SQL pools, and pipelines to Microsoft Fabric. Translates mssparkutils calls to notebookutils (including the env→runtime namespace change), replaces Linked Services with Fabric Data Connections and OneLake Shortcuts, rewrites Dedicated SQL Pool DDL by removing DISTRIBUTION and CLUSTERED COLUMNSTORE hints, substitutes PolyBase external tables with COPY INTO, and maps Synapse Pipeline activities to Fabric Data Pipeline equivalents. Use when the user wants to: (1) port Synapse Spark notebooks to Fabric Lakehouse or Spark Job Definitions, (2) replace mssparkutils or Linked Services in Synapse code, (3) rewrite Dedicated SQL Pool T-SQL for Fabric Warehouse, (4) migrate Synapse Pipelines to Fabric Data Pipelines. Triggers: "migrate from synapse", "synapse to fabric", "mssparkutils to notebookutils", "synapse linked service replacement", "dedicated sql pool to warehouse", "polybase to copy into", "port synapse notebooks", "synapse workspace migration".
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  12. Hdinsight Migration · kimtth bundle
    Port Azure HDInsight Spark clusters and Hive workloads to Microsoft Fabric. Removes legacy HiveContext and standalone SparkContext constructors, replacing them with the pre-instantiated SparkSession. Converts WASB and ABFS storage paths to OneLake abfss URLs via Shortcuts. Transforms Hive DDL (STORED AS ORC, external tables) to Delta Lake schemas inside Fabric Lakehouse. Maps Oozie workflow actions — spark, hive, shell, sqoop, coordinator — to Fabric Pipeline activities and schedule triggers. Introduces notebookutils for file and credential operations previously handled via subprocess or HDFS client calls. Use when the user wants to: (1) retire an HDInsight cluster and move to Fabric, (2) convert WASB paths or Hive DDL, (3) replace Oozie coordinators with Fabric Pipelines. Triggers: "migrate from hdinsight", "hdi to fabric", "hivecontext sparksession fabric", "wasb to onelake", "hive ddl to delta", "oozie to fabric pipelines", "hive metastore lakehouse", "hdinsight spark migration".
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  13. Spark Authoring CLI · kimtth bundle
    Develop Microsoft Fabric Spark/data engineering workflows and write code in Fabric Notebook cells with intelligent routing to specialized resources. Provides workspace/lakehouse management, notebook code authoring (PySpark, Scala, SparkR, SQL), and routes to: data engineering patterns, development workflow, or infrastructure orchestration. Use when the user wants to: (1) manage Fabric workspaces and resources, (2) write or debug code in notebook cells, (3) use notebookutils, (4) develop notebooks and PySpark applications, (5) design data pipelines, (6) provision infrastructure as code. Triggers: "develop notebook", "data engineering", "workspace setup", "pipeline design", "infrastructure provisioning", "Delta Lake patterns", "Spark development", "lakehouse configuration", "write notebook code", "notebookutils", "notebook cell", "PySpark notebook", "%%sql cell", "%%configure", "fabric notebook", "run notebook", "notebook deployment".
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  14. Sqldw Authoring CLI · kimtth bundle
    Execute authoring T-SQL (DDL, DML, data ingestion, transactions, schema changes) against Microsoft Fabric Data Warehouse and SQL endpoints from agentic CLI environments. Use when the user wants to: (1) create/alter/drop tables from terminal, (2) insert/update/delete/merge data via CLI, (3) run COPY INTO or OPENROWSET ingestion, (4) manage transactions or stored procedures, (5) perform schema evolution, (6) use time travel or snapshots, (7) generate ETL/ELT shell scripts, (8) create views/functions/procedures on Lakehouse SQLEP. Triggers: "create table in warehouse", "insert data via T-SQL", "load from ADLS", "COPY INTO", "run ETL with T-SQL", "alter warehouse table", "upsert with T-SQL", "merge into warehouse", "create T-SQL procedure", "warehouse time travel", "recover deleted warehouse data", "create warehouse schema", "deploy warehouse", "transaction conflict", "snapshot isolation error".
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  15. Databricks Migration · kimtth bundle
    Port Databricks notebooks and jobs to Microsoft Fabric. Provides an exhaustive dbutils to notebookutils substitution table: fs operations (mount removal via OneLake Shortcuts), secret scope to Key Vault URL conversion, notebook run and exit, widget replacement with parameter-tagged cells, and library install replacement with Fabric Environments. Covers Unity Catalog three-level namespace reduction to Lakehouse two-level schemas, DBFS path conversion to OneLake, Databricks Jobs to Spark Job Definitions, MLflow tracking URI removal, and Photon to Native Execution Engine substitution. Use when the user wants to: (1) replace dbutils with notebookutils, (2) collapse Unity Catalog namespaces to Lakehouse schemas, (3) convert Databricks Jobs or Delta Live Tables. Triggers: "migrate from databricks", "databricks to fabric", "dbutils to notebookutils", "dbutils fabric", "unity catalog migration", "dbfs to onelake", "databricks notebook migration", "delta live tables fabric", "photon native execution".
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  16. Fabric API Discovery · kimtth
    Discover Fabric APIs, OpenAPI specs, item schemas, and best practices using the Fabric MCP Server. Use when exploring available Fabric workloads, looking up API specifications, finding item definition formats, or managing OneLake files programmatically. All MCP tools run locally for reference.
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  17. Spark Operations CLI · kimtth bundle
    Diagnose failed Spark jobs, unhealthy Livy sessions, and performance bottlenecks in Microsoft Fabric via read-only CLI triage. Use when the user wants to: (1) diagnose why a Spark job, notebook run, or Lakehouse job failed, (2) triage stuck or dead Livy sessions, (3) identify OOM, shuffle spill, or data skew, (4) retrieve driver and executor logs or Spark Advisor findings, (5) copy event logs and start a local Spark History Server, (6) diagnose all Spark activities within a failed pipeline run. Triggers: "diagnose my failed notebook", "why did my spark job fail", "triage spark failure", "diagnose pipeline run failure", "why did my pipeline fail", "livy session stuck in starting", "spark executor OOM", "check spark advisor findings", "shuffle spill diagnosis", "why did my lakehouse job fail", "diagnose lakehouse table load", "data skew diagnosis", "open spark history server locally", "analyze spark failure logs", "spark job triage".
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  18. Sqldw Operations CLI · kimtth bundle
    Analyze Fabric Data Warehouse performance via CLI using sqlcmd and queryinsights views. Diagnose slow queries, SQL pool pressure, cache coldness, and recommend clustering keys. Triggers: "DW slow query analysis", "slowest queries warehouse", "queryinsights long running", "warehouse CPU resource consumers", "SQL pool pressure window", "pressure events warehouse", "DW cache warmth cold start", "cache warmth analysis", "warehouse cluster key recommendation", "cluster tables performance", "DW performance baseline comparison", "performance degraded warehouse", "warehouse user query patterns", "queryinsights diagnostics", "DW optimization sqlcmd".
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  19. Powerbi Authoring CLI · kimtth bundle
    Create, manage, and deploy Power BI semantic models inside Microsoft Fabric workspaces via `az rest` CLI against Fabric and Power BI REST APIs. Use when the user wants to: (1) create a semantic model from TMDL definition files, (2) retrieve or download semantic model definitions, (3) update a semantic model definition with modified TMDL, (4) trigger or manage dataset refresh operations, (5) configure data sources, parameters, or permissions, (6) deploy semantic models between pipeline stages. Covers Fabric Items API (CRUD) and Power BI Datasets API (refresh, data sources, permissions). For read-only DAX queries, use `powerbi-consumption-cli`. For fine-grained modeling changes, route to `powerbi-modeling-mcp`. Triggers: "create semantic model", "upload TMDL", "download semantic model TMDL", "refresh dataset", "semantic model deployment pipeline", "dataset permissions", "list dataset users", "semantic model authoring".
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  20. Spark Consumption CLI · kimtth
    Analyze lakehouse data interactively using Fabric Lakehouse Livy API sessions and PySpark/Spark SQL for advanced analytics, DataFrames, cross-lakehouse joins, Delta time-travel, and unstructured/JSON data. Use when the user explicitly asks for PySpark, Spark DataFrames, Livy sessions, or Python-based analysis — NOT for simple SQL queries. Triggers: "PySpark", "Spark SQL", "analyze with PySpark", "Spark DataFrame", "Livy session", "lakehouse with Python", "PySpark analysis", "PySpark data quality", "Delta time-travel with Spark".
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  21. Sqldw Consumption CLI · kimtth bundle
    Execute read-only T-SQL queries against Fabric Data Warehouse, Lakehouse SQL Endpoints, and Mirrored Databases via CLI. Default skill for any lakehouse data query (row counts, SELECT, filtering, aggregation) unless the user explicitly requests PySpark or Spark DataFrames. Use when the user wants to: (1) query warehouse/lakehouse data, (2) count rows or explore lakehouse tables, (3) discover schemas/columns, (4) generate T-SQL scripts, (5) monitor SQL performance, (6) export results to CSV/JSON. Triggers: "warehouse", "SQL query", "T-SQL", "query warehouse", "show warehouse tables", "show lakehouse tables", "query lakehouse", "lakehouse table", "how many rows", "count rows", "SQL endpoint", "describe warehouse schema", "generate T-SQL script", "warehouse performance", "export SQL data", "connect to warehouse", "lakehouse data", "explore lakehouse".
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  22. Search Consumption CLI · kimtth
    Find and discover Microsoft Fabric items across workspaces when the workspace is unknown. Use when the user wants to: (1) find an item by name across workspaces, (2) list items of specific type across workspaces, (3) identify which workspace contains an item, (4) return item/workspace IDs for downstream API calls. Triggers: "which workspace has", "where is", "what items do I have", "do I have", "find item", "find all items", "search for item", "discover items", "find across workspaces".
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  23. Activator Authoring CLI · kimtth bundle
    Create alerts, notifications, and automated actions on Fabric data and events via Fabric REST API and `az rest` CLI. Use when the user wants to: (1) create, update, or delete an alert or notification flow, (2) send a Teams message, send an email, or run a Fabric item when something happens, (3) connect alert logic to Eventhouse, Eventstream, Real-time Hub, or Digital Twin Builder / Ontology data, (4) adjust thresholds, filters, event triggers, or actions, (5) troubleshoot or change an existing Activator/Reflex definition. Triggers: "create an alert", "notify me when", "let me know when", "take action when", "send me an email when", "send a teams message when", "run a pipeline when", "update an alert", "delete an alert", "activator rule"
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  24. Dataflows Authoring CLI · kimtth bundle
    Create, update, delete, and manage Fabric Dataflows Gen2 artifacts with Power Query M mashup definitions via CLI (az rest / curl). Uses az rest and curl against the Fabric REST API to author definitions containing base64-encoded mashup.pq, queryMetadata.json, and .platform parts. Supports creating dataflows with inline definitions, modifying mashup queries, binding connections, triggering Execute refresh jobs with typed parameter overrides, and exporting definitions for CI/CD. Use when the user wants to: (1) create a new Dataflow Gen2 with Power Query M queries, (2) update a dataflow mashup definition, (3) trigger a dataflow refresh job, (4) bind or manage dataflow connections, (5) set up CI/CD via definition export and import, (6) delete a dataflow, (7) configure staging destinations. Triggers: "create dataflow", "author dataflow", "Power Query M", "mashup document", "update dataflow definition", "refresh dataflow", "dataflow connection", "ETL dataflow", "dataflow CI/CD".
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  25. Powerbi Consumption CLI · kimtth bundle
    The ONLY supported path for read-only Microsoft Fabric Power BI semantic model (formerly "Power BI dataset") query interactions. Execute DAX queries via the MCP server ExecuteQuery tool to: (1) discover semantic model metadata (tables, columns, measures, relationships, hierarchies, etc.) and their properties, (2) retrieve data from a semantic model. Triggers: "DAX query", "semantic model metadata", "list semantic model tables", "run EVALUATE", "get measure expression".
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  26. Eventhouse Authoring CLI · kimtth bundle
    Execute KQL management commands (table management, ingestion, policies, functions, materialized views) against Fabric Eventhouse and KQL Databases via CLI. Use when the user wants to: 1. Create or alter KQL tables, columns, or functions 2. Ingest data into an Eventhouse (inline, from storage, streaming) 3. Configure retention, caching, or partitioning policies 4. Create or manage materialized views and update policies 5. Manage data mappings for ingestion pipelines 6. Deploy KQL schema via scripts Triggers: "create kql table", "kql ingestion", "ingest into eventhouse", "kql function", "materialized view", "kql retention policy", "eventhouse schema", "kql authoring", "create eventhouse table", "kql mapping"
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  27. Microsoft Code Reference · kimtth
    Look up Microsoft API references, find working code samples, and verify SDK code is correct. Use when working with Azure SDKs, .NET libraries, or Microsoft APIs to find the right method, check parameters, get working examples, or troubleshoot errors. Catches hallucinated methods, wrong signatures, and deprecated patterns by querying official docs.
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  28. Activator Consumption CLI · kimtth
    Inspect existing alerts, notifications, and automated actions in Fabric via read-only REST API calls using `az rest` CLI. Use when the user wants to: (1) list existing alerts in a workspace, (2) inspect how an alert or notification is configured, (3) read and decode an Activator/Reflex definition (ReflexEntities.json), (4) list rules, sources, and actions behind an alert, (5) understand why an alert fires or what action it takes. Triggers: "show my alerts", "what alerts do I have", "inspect this alert", "show me the rule", "show me the action", "show me the source", "get reflex definition", "list activators", "activator details"
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  29. Dataflows Consumption CLI · kimtth bundle
    Monitor, inspect, and discover Fabric Dataflows Gen2 via read-only CLI operations (az rest / curl). List dataflows across workspaces, decode base64 definitions to inspect Power Query M queries and queryMetadata.json, discover typed parameters with defaults, poll refresh operations for status, retrieve job history with timing and error details, and classify queries by staging settings. Use when the user wants to: (1) list dataflows, (2) inspect a dataflow definition and decode its mashup, (3) discover parameters, (4) check refresh status, (5) retrieve job history, (6) analyze staging settings, (7) examine connections and data source bindings. Triggers: "dataflow status", "refresh history", "dataflow monitor", "list dataflows", "dataflow parameters", "explore dataflow", "inspect dataflow", "dataflow run status".
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  30. Eventstream Authoring CLI · kimtth
    Create, wire, and publish Microsoft Fabric Eventstream real-time event streaming topologies via the Fabric Items REST API. Build graph-based definitions with 25 source types (Event Hubs, IoT Hub, CDC connectors, Kafka, SampleData), 8 transformation operators (Filter, Aggregate, GroupBy, Join, ManageFields, Union, Expand, SQL), 4 destination types (Lakehouse Delta, Eventhouse, Activator, Custom Endpoint), and DefaultStream/DerivedStream routing. Use when the user wants to: (1) author or publish an Eventstream topology, (2) add CDC sources with SQL-based Debezium payload flattening, (3) assemble multi-table fan-out routing, (4) modify or delete Eventstream definitions. Triggers: "create eventstream", "deploy eventstream", "design eventstream topology", "CDC source", "eventstream operator", "real-time ingestion pipeline", "eventstream definition", "update eventstream".
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  31. E2e Medallion Architecture · kimtth
    Implement end-to-end Medallion Architecture (Bronze/Silver/Gold) lakehouse patterns in Microsoft Fabric using PySpark, Delta Lake, and Fabric Pipelines. Use when the user wants to: (1) design a Bronze/Silver/Gold data lakehouse, (2) set up multi-layer workspace with lakehouses for each tier, (3) build ingestion-to-analytics pipelines with data quality enforcement, (4) optimize Spark configurations per medallion layer, (5) orchestrate Bronze-to-Silver-to-Gold flows via notebooks. Triggers: "medallion architecture", "bronze silver gold", "lakehouse layers", "e2e data pipeline", "end-to-end lakehouse", "data lakehouse pattern", "multi-layer lakehouse", "build medallion", "setup medallion".
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  32. Eventhouse Consumption CLI · kimtth bundle
    Run KQL queries against Fabric Eventhouse for real-time intelligence and time-series analytics using `az rest` against the Kusto REST API. Covers KQL operators (where, summarize, join, render), Eventhouse schema discovery (.show tables), time-series patterns with bin(), and ingestion monitoring. Use when the user wants to: 1. Run read-only KQL queries against an Eventhouse or KQL Database 2. Discover Eventhouse table schema and metadata 3. Analyse real-time or time-series data with KQL operators 4. Monitor ingestion health and active KQL queries 5. Export KQL results to JSON Triggers: "kql query", "kusto query", "eventhouse query", "kql database", "real-time intelligence", "time-series kql", "query eventhouse", "explore eventhouse", "show tables kql"
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  33. Eventstream Consumption CLI · kimtth
    List, inspect, and monitor Microsoft Fabric Eventstream real-time event ingestion pipelines via the Fabric Items REST API. Discover Eventstreams across workspaces, decode base64-encoded graph topologies to trace event flow from source through operators to destination nodes. Validate source connection IDs, destination wiring, retention policies (1-90 days), and throughput levels. Use when the user wants to: (1) list or search Eventstreams in a workspace, (2) decode and trace graph topology from source to destination, (3) validate source and destination configurations, (4) check retention and throughput settings. Triggers: "list eventstreams", "show eventstream", "inspect eventstream", "explain eventstream", "eventstream health", "monitor eventstream", "describe eventstream", "check eventstream configuration", "eventstream retention".
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  34. Dataflows Save As Authoring CLI · kimtth bundle
    Assess, plan, and execute dataflow Gen1 → Gen2.1 CI/CD save-as operations via CLI (az rest / curl) against both Power BI REST and Fabric REST APIs. Scan workspaces or entire tenants for Gen1 dataflows, evaluate save-as readiness with seven risk signals (incremental refresh, BYOSA storage, Power Automate triggers, pipeline dependencies, linked entities, DirectQuery, caller-not-owner), produce a Save-As Readiness Snapshot (markdown + JSON), and invoke the SaveAsNativeArtifact API to create upgraded Gen2.1 copies of Gen1 dataflows. Use when the user wants to: (1) discover Gen1 dataflows in a workspace or tenant, (2) assess save-as readiness and risk signals, (3) upgrade or migrate Gen1 into a Gen2.1 copy, (4) validate post-save-as data integrity, (5) detect residual Gen1 references. Triggers: "save Gen1 dataflow", "convert dataflow Gen1", "upgrade dataflow", "migrate dataflow", "dataflow readiness", "Gen1 to Gen2", "dataflow save-as assessment", "saveAsNativeArtifact", "dataflow save-as scan".
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  35. Go · kimtth
    Use when: write or review idiomatic Go with explicit errors, clear concurrency, and small interfaces.
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  36. Cpp · kimtth
    Use when: write or review modern C++ with RAII, smart pointers, and value semantics.
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  37. PHP · kimtth
    Use when: write or review modern, typed PHP with strict types, clear structure, and safe data handling.
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  38. SQL · kimtth
    Use when: write or review correct, set-based SQL with safe parameters and sensible indexing.
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  39. Bash · kimtth
    Use when: write or review robust shell scripts that fail fast and handle paths and input safely.
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  40. Java · kimtth
    Use when: write or review modern, idiomatic Java with immutability, clear types, and clean structure.
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  41. Ruby · kimtth
    Use when: write or review idiomatic, readable Ruby with clear objects and expressive methods.
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  42. Rust · kimtth
    Use when: write or review idiomatic Rust with sound ownership, error handling, and zero-cost abstractions.
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  43. CI CD · kimtth
    Use when: design or improve a CI/CD pipeline for fast, reliable, automated build-test-deploy.
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  44. Swift · kimtth
    Use when: write or review idiomatic Swift with value types, optionals, and safe concurrency.
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  45. Teach · kimtth
    Use when: explain code or a concept at the right depth for the asker, not a generic lecture.
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  46. Csharp · kimtth
    Use when: write or review modern, idiomatic C# with async, nullable reference types, and clean structure.
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  47. Kotlin · kimtth
    Use when: write or review idiomatic Kotlin with null safety, immutability, and concise expressions.
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  48. Nodejs · kimtth
    Use when: write or review Node.js backends with correct async, error handling, and resource limits.
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  49. Python · kimtth
    Use when: write or review idiomatic, typed, well-structured Python that is easy to test and maintain.
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  50. Shadcn · kimtth
    Use when: add, customize, or extend shadcn/ui components with correct Tailwind and theming setup.
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  51. To Prd · kimtth
    Use when: turn current conversation and repo context into a PRD for an issue tracker.
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  52. GRAPHQL · kimtth
    Use when: design or review GraphQL schemas and resolvers with safe, efficient data access.
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  53. Handoff · kimtth
    Use when: write a handoff so another session or agent can resume work without context loss.
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  54. Mocking · kimtth
    Use when: use test doubles correctly — mock true boundaries, not the code under test.
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  55. Reactjs · kimtth
    Use when: write or review React components with correct hooks, state, effects, and rendering.
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  56. Critique · kimtth
    Use when: give structured, specific design critique with actionable fixes, not vague feedback.
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  57. Grill Me · kimtth
    Use when: pressure-test your own reasoning or a plan before committing to it.
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  58. Refactor · kimtth
    Use when: improve code structure, readability, type safety, or maintainability without changing external behavior.
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  59. Research · kimtth
    Use when: run a systematic literature review and synthesize sourced, well-reasoned findings.
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  60. Zoom Out · kimtth
    Use when: step back from unfamiliar code and map surrounding modules, callers, concepts, and ownership before editing.
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  61. To Issues · kimtth
    Use when: break a plan, spec, or PRD into independently grabbable implementation issues.
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  62. Turborepo · kimtth
    Use when: configure a Turborepo monorepo with task pipelines, caching, and affected-only runs.
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  63. API Design · kimtth
    Use when: design a clear, consistent, and evolvable API contract before implementing it.
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  64. Git Bisect · kimtth
    Use when: find the commit that introduced a bug with a binary search over history.
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  65. Git Commit · kimtth
    Use when: create a conventional git commit from the current diff with logical staging and message analysis.
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  66. Git Rebase · kimtth
    Use when: clean up or reorder commits with rebase while keeping history safe and reviewable.
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  67. Skills CLI · kimtth
    Use when: discover, install, list, check, update, remove, back up, restore, sync, or initialize Agent Skills with bunx/npx skills.
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  68. Typescript · kimtth
    Use when: write or review TypeScript that maximizes type safety without fighting the compiler.
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  69. Concurrency · kimtth
    Use when: write or review concurrent code that avoids races, deadlocks, and shared-state bugs.
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  70. Drizzle Orm · kimtth
    Use when: define type-safe schemas, migrations, and queries with Drizzle ORM and full TS inference.
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  71. Find Skills · kimtth
    Use when: find, compare, install, update, or remove agent skills from skills.sh or a source repo.
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  72. Watch Video · kimtth
    Use when: answer questions about a video URL or local file by seeing its frames and reading its transcript.
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  73. Agent Memory · kimtth
    Use when: persist and recall context across coding sessions so the agent stops re-learning the same stack, bugs, and decisions.
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  74. Duckdb Query · kimtth
    Use when: run analytical queries in-process over files, Parquet, or CSV with DuckDB.
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  75. Load Testing · kimtth
    Use when: measure system behavior under load to find limits, bottlenecks, and regressions.
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  76. Authorization · kimtth
    Use when: design or review access control so users can only do what they are permitted to do.
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  77. Brainstorming · kimtth
    Use when: explore options or decompose an ambiguous problem before committing to one approach.
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  78. Observability · kimtth
    Use when: instrument a system with logs, metrics, and traces to understand it in production.
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  79. Rate Limiting · kimtth
    Use when: protect a service with rate limiting and backpressure without harming legitimate users.
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  80. Write A Skill · kimtth
    Use when: create or improve an agent skill with proper frontmatter, structure, triggers, and progressive disclosure.
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  81. Writing Plans · kimtth
    Use when: write a structured implementation plan before starting a complex or multi-step task.
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  82. Authentication · kimtth
    Use when: implement or review authentication flows, sessions, tokens, and password handling securely.
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  83. Clean Codebase · kimtth
    Clean up dead code, obsolete paths, and contradictions in the codebase to keep it small, correct, and aligned with reality.
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  84. Docker Compose · kimtth
    Use when: define multi-service local and test environments with Docker Compose reliably.
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  85. Error Handling · kimtth
    Use when: design error handling so failures are explicit, recoverable, and never silently swallowed.
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  86. Github Actions · kimtth
    Use when: write or review GitHub Actions workflows that are fast, secure, and maintainable.
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  87. Webapp Testing · kimtth
    Use when: test a web app across unit, integration, and end-to-end layers with the right balance.
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  88. Chrome Devtools · kimtth
    Use when: debug, inspect, automate, screenshot, profile, or analyze a web page with Chrome DevTools-style browser tools.
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  89. Design Patterns · kimtth
    Use when: apply a design pattern to a real problem without over-engineering the solution.
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  90. Executing Plans · kimtth
    Use when: execute a written implementation plan with checkpoints, verification, and blocker handling.
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  91. Frontend Design · kimtth
    Use when: build or reshape UI with distinctive, intentional visual design instead of generic defaults.
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  92. Grill With Docs · kimtth
    Use when: verify claims or API usage against fetched official documentation, not memory.
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  93. REST API Design · kimtth
    Use when: design RESTful HTTP APIs with correct resources, methods, status codes, and pagination.
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  94. Security Review · kimtth
    Use when: review code or a design for security issues across the OWASP Top 10 and common pitfalls.
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  95. Threat Modeling · kimtth
    Use when: systematically identify threats to a system and decide how to mitigate them.
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  96. Input Validation · kimtth
    Use when: validate and sanitize untrusted input at boundaries to prevent bad data and attacks.
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  97. Solid Principles · kimtth
    Use when: apply SOLID principles to make object-oriented code flexible and maintainable.
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  98. State Management · kimtth
    Use when: choose and structure client state so data stays consistent and predictable.
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  99. Caching Strategies · kimtth
    Use when: add caching with the right layer, key design, invalidation, and consistency trade-offs.
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  100. Clean Architecture · kimtth
    Use when: structure an app so business logic is independent of frameworks, UI, and databases.
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