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Found 102 Skills
Performance attribution, trade analytics, and strategy optimization
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore. Use when invoking models, setting up Knowledge Bases, creating agents, applying guardrails, deploying to AgentCore, troubleshooting Bedrock errors (ThrottlingException, AccessDeniedException), or choosing models (Claude, Llama, Nova, Titan). ALSO USE for prompt caching setup and debugging, quota health checks and throttling diagnosis, cost attribution and tracking, migrating between Claude model generations (4.5 to 4.6 to 4.7), chunking strategies, API selection (Converse vs InvokeModel), guardrail capabilities, and model selection. NOT for custom model training, Rekognition, or Comprehend.
Remove AI generation traces from text. Suitable for editing or reviewing text to make it sound more natural and more like human writing. This is a comprehensive guide based on Wikipedia's "Signs of AI writing". It detects and fixes the following patterns: exaggerated symbolic meaning, promotional language, superficial analysis ending in -ing, vague attribution, overuse of em dashes, rule of three, AI vocabulary, negative parallelism, excessive connecting phrases.
This skill should be used when the user asks to "remove AI writing patterns", "humanize this text", "make this sound more natural", "remove AI-generated traces", "fix robotic writing", or needs to eliminate AI writing patterns from prose. Supports both English and Chinese text. Based on Wikipedia's "Signs of AI writing" guide, detects and fixes inflated symbolism, promotional language, superficial -ing analyses, vague attributions, AI vocabulary, negative parallelisms, and excessive conjunctive phrases.
Remove signs of AI-generated writing from text (formerly human-writing). Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Use when building or fixing B2B pipeline. Revenue-aligned demand generation with lead types, funnel design, conversion paths, scoring/routing, attribution, ABS motions, and compliance.
Content strategy and operations for marketing teams. Positioning, messaging hierarchy, content pillars, editorial calendars, trust-building content, brand architecture, GEO/AI discovery, and content ROI measurement. Use for positioning sprints, trust audits, messaging matrices, content pillar planning, editorial ops, or ROI attribution (including regulated industries).
Remove AI-generated traces from text. Suitable for editing or reviewing text to make it sound more natural and human-written. A comprehensive guide based on Wikipedia's "Signs of AI Writing". Detect and fix the following patterns: exaggerated symbolism, promotional language, superficial analysis ending with -ing, vague attribution, overuse of dashes, rule of three, AI vocabulary, negative parallelism, excessive connective phrases.
Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases.
Toolkit for generating PowerToys release notes from GitHub milestone PRs or commit ranges. Use when asked to create release notes, summarize milestone PRs, generate changelog, prepare release documentation, request Copilot reviews for PRs, update README for a new release, manage PR milestones, or collect PRs between commits/tags. Supports PR collection by milestone or commit range, milestone assignment, grouping by label, summarization with external contributor attribution, and README version bumping.
Grafana Cloud cost management — usage monitoring, cost attribution by label, usage alerts, invoice management, and optimization strategies. Covers Adaptive Metrics (cardinality reduction), Adaptive Logs (log filtering), cost attribution labels, and the FOCUS-compliant billing application. Use when analyzing Grafana Cloud spending, setting up cost alerts, attributing costs to teams, reducing metric/log cardinality, or forecasting observability budgets.