Total 43,865 skills
Showing 12 of 43865 skills
Different techniques to optimize the performance of Qdrant, including indexing strategies, query optimization, and hardware considerations. Use when you want to improve the speed and efficiency of your Qdrant deployment.
Diagnoses and improves Qdrant search relevance. Use when someone reports 'search results are bad', 'wrong results', 'low precision', 'low recall', 'irrelevant matches', 'missing expected results', or asks 'how to improve search quality?', 'which embedding model?', 'should I use hybrid search?', 'should I use reranking?'. Also use when search quality degrades after quantization, model change, or data growth.
Generate images or videos using Jimeng Dreamina CLI. Invoke when user needs to generate images or videos using Jimeng (Dreamina).
Text Storyboard: The translation layer from script to screen, which converts abstract literary works into concrete audio-visual descriptions. It is invoked when users need to convert novels or scripts into text storyboards.
Use when the user wants to deploy and run a prepared AWS FIS experiment. Triggers on "execute FIS experiment", "run FIS experiment", "start chaos experiment", "deploy FIS template", "启动 FIS 实验", "运行混沌实验", "执行故障注入实验", "deploy and run the experiment in [directory]". Expects a prepared experiment directory (from aws-fis-experiment-prepare or manually created) containing experiment-template.json, iam-policy.json, cfn-template.yaml, and alarm configs. Deploys resources via CLI or CloudFormation, starts the experiment with strict user confirmation, monitors progress, and generates results report.
Lacanian psychoanalysis dialogue. Conduct analytical dialogues based on Lacanian theoretical framework (big Other, desire, fantasy, signifier chain). Trigger methods: /lacan, "Lacan", "psychoanalysis dialogue" Lacanian psychoanalysis dialogue using Lacanian framework (big Other, desire, fantasy, signifier chain). Trigger: /lacan, "Lacanian analysis", "psychoanalysis dialogue"
Validate and sanitize user input to prevent XSS, injection attacks, and ensure data quality. Use this skill when you need to validate forms, sanitize user input, prevent cross-site scripting, use Zod schemas, or handle any user-generated content. Triggers include "input validation", "validate input", "XSS", "cross-site scripting", "sanitize", "Zod", "injection prevention", "validateRequest", "safeTextSchema", "user input security".
Internal downstream skill for ctf-sandbox-orchestrator. CTF-sandbox workflow for Linux credential artifacts, service tokens, SSH material, cloud and container secrets, socket-level trust, and host-to-host pivot chains. Use when the user asks to trace Linux auth artifacts, accepted token or key replay, socket or service-account trust edges, sudo or capability abuse, or explain lateral movement across Linux challenge nodes. Use only after `$ctf-sandbox-orchestrator` has already established sandbox assumptions and routed here.
Detect antibot vendors on one or more URLs without opening a browser session. Use when the user asks what antibot, bot protection, WAF, captcha, or challenge provider a site uses, or asks to check sites for Cloudflare, Akamai, DataDome, PerimeterX, Imperva/Incapsula, Kasada, reCAPTCHA, hCaptcha, Anubis, or Shape Security markers.
Execute and manage Athena SQL queries across default and federated catalogs (Glue, S3 Tables, Redshift). Triggers on phrases like: query data, run SQL, athena query, analyze table, SQL query, workgroup status, profile table, query Redshift catalog, query S3 Tables. Do NOT use for finding specific data assets (use finding-data-lake-assets), full catalog audits (use exploring-data-catalog), importing data (use ingesting-into-data-lake).
Full inventory and audit of AWS Glue Data Catalog assets across S3 Tables, Redshift-federated, and remote Iceberg catalogs. Triggers on: inventory the catalog, audit databases, list all tables, catalog overview, data landscape, enumerate catalogs, data inventory, search the catalog. Do NOT use for finding specific data (use finding-data-lake-assets), running queries (use querying-data-lake), or creating tables (use creating-data-lake-table).
Import data into the AWS data lake from S3 files, local uploads, JDBC databases (Oracle, SQL Server, PostgreSQL, MySQL, RDS, Aurora), Amazon Redshift, Snowflake, BigQuery, DynamoDB, or existing Glue catalog tables (migration). Default target is S3 Tables; standard Iceberg on a general purpose bucket is supported where S3 Tables is not adopted. Handles one-time loads, recurring pipelines, migrations. Triggers on: import data, load data, ingest, sync database, migrate table, move data to AWS, set up pipeline, ETL, pull from Snowflake, query BigQuery into S3, export DynamoDB, CTAS, convert to Iceberg. Do NOT use for setting up or troubleshooting Glue connections (use connecting-to-data-source), creating empty tables (use creating-data-lake-table), running queries (use querying-data-lake), finding tables by fuzzy name (use finding-data-lake-assets), catalog audit (use exploring-data-catalog), or SaaS platforms like Salesforce, ServiceNow, SAP, MongoDB, Kafka.