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Assess reported phishing emails by checking sender authentication, links, and attachments. Post a risk rating, supporting evidence, and a recommended action to Slack, leaving blocking, deletion, and other changes to the security team.
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Route code changes and SQL analysis to isolated Kortix work sessions with clear requirements and workspace details. Coordinate parallel investigations or independent pull request reviews, then summarize deliverables, verification results, and differences between findings.
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Audit PHP and other source code by listing calls to known dangerous functions, checking for enumeration gaps, and examining input paths and safeguards. Store risk assessments and verdicts in a searchable audit ledger.
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Investigate slow PostgreSQL and MySQL queries using execution plans, which show how the database runs a query. Develop index, SQL, and configuration changes, then compare measurements before and after each change to validate the results.
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Manage Hugging Face Hub through the hf command line tool. Download and upload models or datasets, organize cloud storage, manage authentication and local caches, run scheduled jobs, and deploy or maintain model inference services.
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Write Apache Cassandra distributed tests that simulate multiple nodes within one JVM, the Java runtime. The guide covers cluster setup, queries, node restarts, message dropping for failure scenarios, and troubleshooting problems caused by isolated class loading.
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Investigate errors and health in a running Convex app using plain-language questions. It summarizes relevant logs with counts and representative evidence, checks deployment timing, and provides dashboard links when possible for verification.
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Create tests for Convex functions with convex-test and vitest, using a backend that runs in memory. Check arguments, return values, authentication, indexes, errors, and scheduled functions without relying on real time or network access.
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Use Chainbase CLI to investigate blockchain records, including token holders, prices, wallet activity, and DeFi positions. Use Tops to discover trending crypto topics, inspect related posts, and track recent Twitter/X mentions of projects or keywords.
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Build an MCP integration skill using a template that reads server-specific reference notes before calling tools. The Sentry example gathers unresolved errors, groups them by likely root cause, and produces a report with investigation suggestions.
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Find and reuse organization-approved skills, prompts, tool connections, and Agents through Observal. Check existing installations, select resources suited to the task, and handle account setup, shared Agents, inbox items, and teamspace membership through the CLI.
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Edit Unity scenes and assets with RQL, a query language for selecting targets and applying changes. Preview bulk edits, change properties, or create and remove objects, with validation, Editor undo, and automatic saving.
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Build, validate, and release Marina applications and reports, then load or query their Postgres data. Manage application revisions, preview changes locally, roll back to retained packages, or archive applications through the Marina command line.
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Build DOCA applications that send and receive network packets directly from CUDA code on an NVIDIA GPU. Get guidance on connecting queues, registering GPU memory, checking hardware capabilities, and diagnosing GPUNetIO setup and runtime errors.
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Runs SQL analytics on SageMaker Catalog asset metadata tables exported as Apache Iceberg in S3 Tables. Covers governance queries, asset growth tracking, ownership audits, time-travel over catalog state, and metadata quality analysis. Applies when querying catalog inventory, finding assets without descriptions, comparing catalog snapshots, or auditing data ownership. Trigger phrases: catalog inventory SQL, how many assets, assets without descriptions, asset growth over time, who owns this data, catalog governance, data quality audit, catalog analytics.
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Use whenever datasets, cloud storage buckets, or data pipelines are mentioned — creating, saving, querying, listing, exploring, deleting, or processing data in S3, GCS, Azure Blob, or local storage. Also use when running any script that may create datasets as a side effect. Maintains a knowledge base at dc-knowledge/ (JSON + markdown). ALWAYS use this skill when the user creates a dataset, saves pipeline output, runs a data script, or references any storage bucket.
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Query images with a local Ollama vision model without loading the image into the main agent context. Use when you need to describe a screenshot, check whether rendered content is present, detect overlapping elements, or ask any visual question about a PNG/JPEG/WebP file. Requires Ollama running locally with the Gemma 4 multimodal model (`gemma4` on Ollama). Script: .agents/skills/vision/scripts/ask.py. Trigger phrases: "describe image", "what does this screenshot show", "does the canvas contain content", "check screenshot visually", "look at this image", "any overlapping elements", "vision query".
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Query a user's Gemini Notebook (formerly NotebookLM) for source-grounded answers through a logged-in browser session on their Google account. Uses the account's usage limits and writes browser state. Runs only on an explicit request: /blog notebooklm, "ask my Gemini Notebook", "ask my NotebookLM notebook", or "query my notebook library". Also used by blog-write when the user named a notebook for research. Not for generic research or note-taking.
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Reads, searches and exports local Claude Code and Kimi CLI history without resuming work: timelines, verbatim user input, keyword or fuzzy recall, file recovery from transcripts, and which session ran a given command in a known time window. Use when the user asks what was said, wants a session ID or original context, needs proof of what a session contained, or needs past-session runtime evidence about commands, tool calls and hook runs — query this index instead of raw-scanning transcript files. Not for Codex (use read-codex-history); with no platform or several named, start at local-conversation-history.
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Manages a Fabric SQL database item, the OLTP SQL Server engine, including running T-SQL through sqlcmd, temporal and vector similarity search, schema and sys.tables inspection, dacpac deployment, and Query Store, blocked sessions and regressed-plan investigation. Use for any query or change against a SQL database item. Warehouse, lakehouse SQL endpoint and mirrored items belong to sqldw-cli.
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Expert guidance for the cross-platform Tabular Editor CLI (the `te` binary, currently in preview) that manages Power BI / Analysis Services semantic models from the terminal on macOS, Linux, and Windows. Use when the user mentions the `te` CLI or "Tabular Editor CLI" (not the "2"), or runs a `te <command>` to scaffold, inspect, edit, validate, run BPA on, query, deploy, refresh, test, or migrate a semantic model. Not for the legacy Windows-only `TabularEditor.exe` (TE2).
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Query and answer questions about Volcengine API specifications. Trigger this skill whenever a user asks about Volcengine API parameters, error codes, request methods, enum values, required fields, response structures, pagination, parameter dependencies, or API comparisons — even if they don't explicitly say "API". Typical triggers include questions like "What parameters does DescribeInstances have?", "What values does Status support?", "What does InvalidInstanceId.NotFound mean?", "Does Volcengine have a batch tag deletion API?", "Which APIs does ECS support?", "How do I pass parameters to CreateDatabase?", "Is ChargeType required?", "What fields does DescribeInstances return?", "How do I paginate instance lists?", "What's the difference between these two APIs?", "RunInstances returns InvalidParameterValue". When the user needs runnable SDK code, hand off to the volcengine-sdk-generator skill. When the user needs CLI-based operations, hand off to the volcengine-cli skill. Supports both Chinese and English prompts.
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Model-guided autonomous root-cause analysis over a UModel object-graph semantic layer. Use with `umodel-query` when diagnosing service degradation, SLO breach, latency/error spikes, incidents, outages, or questions like why a service is slow, degraded, erroring, or timing out. The skill guides evidence collection across object graph, metrics, logs, topology, runbooks, deployments, config changes, business traffic, and runtime capacity; it is especially useful for ruling out red herrings such as recent but unrelated deployments. Triggers: root cause, RCA, incident, SLO breach, outage, postmortem, latency spike, error spike, timeout, 根因分析, 故障排查, 告警定位, 为什么慢, SLO 击穿.
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Query and download NCI Imaging Data Commons (IDC) cancer radiology and pathology datasets via the idc-index Python client. No authentication required: the parquet index ships inside the pip wheel, SQL runs locally via DuckDB, and DICOM downloads stream from public S3/GCS buckets through s5cmd. Use sql_query() for DuckDB cohort selection, get_collections/get_patients/get_dicom_studies/get_dicom_series for hierarchical browsing, download_from_selection() for downloads, and get_viewer_URL() for OHIF/Slim links. Use pydicom-medical-imaging for local DICOM reading; histolab for whole-slide pathology preprocessing.
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