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Found 2,069 Skills
Create a comprehensive brand standards document — covering logo usage, color, typography, voice, messaging, and application rules. Use when the user says "brand guidelines", "brand standards", "brand book", "style guide", "brand guide", "brand manual", "brand rules", "brand documentation", "brand toolkit", "onboarding designers or copywriters", "need a document for the team", "brand consistency across teams", or wants to codify all brand decisions into a reusable reference document.
Routes tasks related to reverse engineering, exploitation, penetration testing, malware, mobile security, firmware analysis, browser automation, documentation, and other security domains to the appropriate specialized skill modules. Use this when a task spans multiple modules or the correct entry point for reverse engineering skills is unclear.
Query and analyze a Dynatrace tenant's ACTUAL billing and usage data with DQL against dt.system.events — DPS consumption breakdown, cost-normalized spend ranking, included volume deduction, chargeback/showback, cost drivers, spending trends, cost investigation, metrics ingest optimization, query cost attribution, workflow total cost, and entity-level cost drill-down (RUM, hosts, synthetic, K8s). Also directs licensing/entitlement questions to the right resource (not available via DQL). USE ONLY to query/analyze the tenant's actual consumption. Do NOT use for conceptual 'explain' questions about how DPS billing/pricing works or what units/weights/the rate card mean — those belong to Dynatrace documentation. Also do NOT use for making a DQL query itself faster or cheaper to run (query optimization, reducing scanned data/consumption per run, filter-early best practices) — that belongs to dt-dql-essentials. This skill only MEASURES recorded consumption; it does not tune queries.
Use when creating or editing skills, before deployment, to verify they work under pressure and resist rationalization - applies RED-GREEN-REFACTOR cycle to process documentation by running baseline without skill, writing to address failures, iterating to close loopholes
Universal documentation sync for skills, agents, markdown. Modes - status, init, global, project, file, folder.
Assign CPT and HCPCS Level II procedure codes from clinical documentation the way a professional coder builds the claim. Use when users say "code this encounter for procedures", "what CPT codes apply", "assign HCPCS codes", "code this op note", or when turning visit notes or operative reports into claim-ready procedure codes.
Search context-mode's persistent FTS5 knowledge base for previously indexed local project content, documentation, or session memory. Trigger: /context-mode:ctx-search
Databricks documentation reference via llms.txt index. Use when other skills do not cover a topic, looking up unfamiliar Databricks features, or needing authoritative docs on APIs, configurations, or platform capabilities.
Interactive learning system for NetSuite SDF development. Features six modes (learn, review, explain, annotate, quiz, and final) with SAFE Guide integration. Produces compliance-reviewed learning documentation. Learn topics like governance, N/cache, and security directly from SAFE Guide principles. Generate quizzes from code or SAFE Guide content.
Design, create, update, validate, and audit Codex/CCFA skills, trigger wording, resources, references, scripts, path privacy, family governance, and CCFA documentation SVG diagrams. Use for skill maintenance, new skill creation, routing conflict cleanup, Markdown/SVG docs maintenance, and release validation. Do not perform research writing or review work.
Convert natural language questions into safe executable SQL to query Ascend PyTorch Profiler / msprof database for operator time consumption, communication, dispatch, and other performance data. Supports table schema extraction from official documentation. Use this skill when the user wants to: (1) analyze Ascend profiling database, (2) query operator performance data, (3) analyze communication and dispatch bottlenecks, (4) check table schema for profiling data. Trigger: user mentions "profiler db", "sqlite", "sql", "table", "schema", "ascend-pytorch-profiler", "msprof", "operator time", "communication time", "dispatch analysis", "性能分析", "算子耗时", "数据库查询", "性能数据", "性能瓶颈"
Write meaningful documentation that explains why not what; focus on complex business logic and self-documenting code