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computer-vision-engineer/references/ai-skills.md
skillfactor-pipeline 9b21178015 feat: computer-vision-engineer skill package v0.1.0
2026-08-14 17:28:44 +02:00

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External AI agent skills — computer-vision-engineer

Proven, publicly available AI agent skills mapped to this occupation. Nothing is copied from the sources: every entry is a name, a one-line summary and a link to the upstream skill package. Each section names its source repository, commit, license and retrieval date.

Tiers: core = the skill directly exercises a top market hard skill, tool or method (from gated job-ad evidence) or an essential ESCO competence of this occupation; adjacent = plausibly useful, secondary. Entries are capped at 12 per source and 80 in total per occupation (core first, strongest matches survive); everything beyond the caps is excluded and logged in the pipeline audit trail, not in this package.

Matched deterministically (ISCO group + title/competence keywords, tiered against market evidence + ESCO essentials) by pipeline/p5_enrich_ai_skills.py on 2026-07-14.

Source: anthropics/skills

  • Repository: https://github.com/anthropics/skills (commit f6656c1, retrieved 2026-07-14)
  • License: Apache-2.0; the document skills (docx/pdf/pptx/xlsx) are source-available — see the LICENSE.txt in the upstream skill folder
Skill Tier What it adds Upstream
mcp-builder core Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python … source
claude-api adjacent Reference for the Claude API / Anthropic SDK — model ids, pricing, params, streaming, tool use, MCP, agents, caching, token counting, model migration. TRIGGER — read BEFORE opening the target file; don't skip because it "looks like a … source
webapp-testing adjacent Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs. source
docx adjacent Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files) or Word templates (.dotx files). Triggers include: any mention of 'Word doc', 'word document', '.docx', '.dotx', or requests to … source
pdf adjacent Use this skill whenever the user wants to do anything with PDF files. This includes reading or extracting text/tables from PDFs, combining or merging multiple PDFs into one, splitting PDFs apart, rotating pages, adding watermarks, creating … source
skill-creator adjacent Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with … source

Source: obra/superpowers

Skill Tier What it adds Upstream
brainstorming adjacent You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation. source
subagent-driven-development adjacent Use when executing implementation plans with independent tasks in the current session source
finishing-a-development-branch adjacent Use when implementation is complete, all tests pass, and you need to decide how to integrate the work - guides completion of development work by presenting structured options for merge, PR, or cleanup source
test-driven-development adjacent Use when implementing any feature or bugfix, before writing implementation code source
using-git-worktrees adjacent Use when starting feature work that needs isolation from current workspace or before executing implementation plans - ensures an isolated workspace exists via native tools or git worktree fallback source
executing-plans adjacent Use when you have a written implementation plan to execute in a separate session with review checkpoints source
receiving-code-review adjacent Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation source
requesting-code-review adjacent Use when completing tasks, implementing major features, or before merging to verify work meets requirements source
writing-plans adjacent Use when you have a spec or requirements for a multi-step task, before touching code source
writing-skills adjacent Use when creating new skills, editing existing skills, or verifying skills work before deployment source
dispatching-parallel-agents adjacent Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies source
systematic-debugging adjacent Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes source

Source: wshobson/agents

Skill Tier What it adds Upstream
recsys-pipeline-architect core Design composable recommendation, ranking, and feed pipelines using the six-stage Source→Hydrator→Filter→Scorer→Selector→SideEffect framework popularized by xAI's open-sourced X For You algorithm. Use when building any system that picks … source
prompt-engineering-patterns core This skill should be used when the user asks to "optimize a prompt", "improve prompt performance", "design a prompt template", "write better prompts", "debug prompt issues", "use chain-of-thought", "structured prompting", "few-shot … source
code-documentation-docs-architect (agent) core Creates comprehensive technical documentation from existing codebases. Analyzes architecture, design patterns, and implementation details to produce long-form technical manuals and ebooks. Use PROACTIVELY for system documentation, … source
codebase-cleanup-test-automator (agent) core Master AI-powered test automation with modern frameworks, self-healing tests, and comprehensive quality engineering. Build scalable testing strategies with advanced CI/CD integration. Use PROACTIVELY for testing automation or quality … source
dbt-transformation-patterns core Master dbt (data build tool) for analytics engineering with model organization, testing, documentation, and incremental strategies. Use when building data transformations, creating data models, or implementing analytics engineering best … source
debugging-strategies core Master systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior. source
python-design-patterns core Python design patterns including KISS, Separation of Concerns, Single Responsibility, and composition over inheritance. Use this skill when designing a new service or component from scratch and choosing how to layer responsibilities, when … source
python-testing-patterns core Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices. source
unit-testing-test-automator (agent) core Master AI-powered test automation with modern frameworks, self-healing tests, and comprehensive quality engineering. Build scalable testing strategies with advanced CI/CD integration. Use PROACTIVELY for testing automation or quality … source
async-python-patterns core Master Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations. source
python-background-jobs core Python background job patterns including task queues, workers, and event-driven architecture. Use when implementing async task processing, job queues, long-running operations, or decoupling work from request/response cycles. source
python-error-handling core Python error handling patterns including input validation, exception hierarchies, and partial failure handling. Use when implementing validation logic, designing exception strategies, handling batch processing failures, or building robust … source

Source: google/skills

Skill Tier What it adds Upstream
bigquery-ai-ml core Leverages BigQuery's built-in machine learning and GenAI capabilities for advanced data analytics. Use when you need to write SQL queries that perform time-series forecasting, detect outliers, find key drivers, or leverage generative AI … source
agent-platform-eval-flywheel core Measures and improves the quality of AI models and agents on Google Cloud using the Eval Quality Flywheel methodology. Use when evaluating an agent or model, building an eval dataset, picking or writing evaluation metrics, analyzing … source
bigtable-basics core Assists in provisioning instances/tables, designing performant schemas, and querying data in Bigtable. Use when designing Bigtable row keys, configuring column families, writing SQL queries or client library code (Java, Go, Python) for … source
cloud-sql-basics core This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server … source
bigquery-basics adjacent Manages datasets, tables, and jobs in BigQuery. Use when you need to interact with BigQuery, run SQL queries, manage BigQuery resources (datasets, tables, views), or perform basic data ingestion and analysis. source
datalineage-bigquery-asset-impact-analysis adjacent Analyzes the downstream impact (blast radius) when a BigQuery table or view is broken, stale, or modified. Identifies all downstream tables, dashboards, and processes that will be affected. Use when: - Performing a blast radius or impact … source
alloydb-basics adjacent Manages clusters, instances, and backups for AlloyDB for PostgreSQL, and integrates with AlloyDB model context protocol (MCP) tools for automated database operations. source
agent-platform-alert-configuration adjacent Configures best-practice alerting policies for Google Cloud Vertex AI / Agent Platform agents on Agent Runtime. Use when analyzing, writing, or deploying alerting policies to monitor agent latency, error rates, and quality metrics … source
gke-observability adjacent Configures GKE observability, including Cloud Logging, Cloud Monitoring, and managed Prometheus. Use when configuring GKE monitoring, setting up GKE logging, or configuring Prometheus metrics collection. Don't use to configure local … source
google-analytics-admin-api-basics adjacent Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need … source
google-analytics-data-api-basics adjacent Manages Google Analytics reporting data, enables the Analytics Data API via the Cloud CLI, and creates reports using the Google Analytics Data API (v1beta). Use when you need to interact with Google Analytics properties, run customized … source
google-cloud-networking-observability adjacent Investigates Google Cloud networking issues by analyzing logs, metrics, and diagnostics. Use when investigating VPC Flow Logs (including cost estimation), NAT, firewall, or threat logs, querying latency and throughput metrics, or running … source

Source: czlonkowski/n8n-skills

Skill Tier What it adds Upstream
n8n-code-python core Write Python code in n8n Code nodes. Use when writing Python in n8n, using _input/_json/_node syntax, working with standard library, or need to understand Python limitations in n8n Code nodes. Use this skill when the user specifically … source
n8n-code-tool core Write JavaScript or Python for the n8n Custom Code Tool (@n8n/n8n-nodes-langchain.toolCode) — the AI-agent-callable tool, NOT the workflow Code node. Use when building a Code Tool attached to an AI Agent, writing code that an LLM will … source
n8n-node-configuration adjacent Operation-aware node configuration guidance. Use when configuring nodes, understanding property dependencies, determining required fields, choosing between get_node detail levels, or learning common configuration patterns by node type. … source
n8n-agents adjacent Design n8n AI agents the right way. Use when building or editing any @n8n/n8n-nodes-langchain.* AI node — an AI Agent, LLM chain, Text Classifier, or Information Extractor — and whenever the user mentions AI agents, LLM with tools, tool … source
n8n-binary-and-data adjacent Handle files and binary data in n8n correctly. Use when working with files, images, PDFs, attachments, uploads or downloads, base64, vision/multimodal input, or when an AI agent needs a file as tool input or output — and whenever the user … source
n8n-workflow-patterns adjacent Proven workflow architectural patterns from real n8n workflows. Use when building new workflows, designing workflow structure, choosing workflow patterns, planning workflow architecture, or asking about webhook processing, HTTP API … source
n8n-validation-expert adjacent Interpret validation errors and guide fixing them. Use when encountering validation errors, validation warnings, false positives, operator structure issues, or need help understanding validation results. Also use when asking about … source
n8n-mcp-tools-expert adjacent Expert guide for using n8n-mcp MCP tools effectively. Use when searching for nodes, validating configurations, accessing templates, managing workflows, managing credentials, auditing instance security, or using any n8n-mcp tool. Provides … source
n8n-subworkflows adjacent Build reusable, composable n8n sub-workflows. Use when extracting shared logic, building anything multi-step or reused across workflows, or any workflow over ~10 nodes — and whenever the user mentions sub-workflows, Execute Workflow, … source
n8n-code-javascript adjacent Write JavaScript code in n8n Code nodes. Use when writing JavaScript in n8n, using $input/$json/$node syntax, making HTTP requests with this.helpers / the $helpers global, working with dates using DateTime, troubleshooting Code node … source
n8n-error-handling adjacent Wire n8n error handling so failures are loud, structured, and recoverable. Use when building any webhook/API workflow, a scheduled or unattended workflow, or any path where a silent failure would drop user-visible work — and whenever the … source
n8n-expression-syntax adjacent Validate n8n expression syntax and fix common errors. Use when writing n8n expressions, using {{}} syntax, accessing $json/$node variables, troubleshooting expression errors, mapping data between nodes, or referencing webhook data in … source

Source: NVIDIA/skills

Skill Tier What it adds Upstream
deepstream-dev core NVIDIA DeepStream SDK 9.0 development with Python pyservicemaker API. Use when building video analytics pipelines, GStreamer-based video processing, TensorRT inference integration, object detection/tracking, or Kafka/message broker … source
tao-finetune-clip core CLIP vision-language model for image-text retrieval, zero-shot classification, embedding extraction, ONNX export, and TensorRT deployment. Use when fine-tuning or training CLIP, running zero-shot classification, computing image embeddings, … source
tao-port-huggingface-model core Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). Use when the user asks to "integrate a HuggingFace model into TAO", "add an HF model … source
tao-train-visual-changenet core Visual ChangeNet for binary image classification and segmentation in AOI defect detection. Use when training, evaluating, exporting, or running inference for PCB defect detection or visual inspection, comparing image pairs for PASS/NO_PASS … source
deepstream-generate-pipeline core Build DeepStream GStreamer pipelines interactively. Use when the user asks about pipelines for video/image inference, detection, tracking, or streaming — including natural phrases like 'pipeline to infer on image', 'run inference on … source
tao-train-mask2former core Mask2Former for universal image segmentation (panoptic, instance, and semantic). Transformer-based with masked attention for high-quality segmentation results. Use when training, evaluating, exporting, quantizing, or running inference for … source
tao-train-pointpillars core PointPillars for 3D object detection from LiDAR point clouds. Encodes point clouds into a pseudo-image via a pillar-based representation, then applies 2D detection — used in autonomous driving and robotics. Use when training, evaluating, … source
tilegym-cutile-python core Expert cuTile programming assistant. Write high-performance GPU kernels using cuTile's tile-based programming model with proper validation and optimization. Supports deep agent orchestration for complex multi-kernel tasks. source
tao-train-deformable-detr core Deformable DETR for 2D object detection. Uses deformable attention for efficient multi-scale feature processing, lighter than DINO with competitive accuracy. Use when training, evaluating, exporting, quantizing, or running inference for a … source
tao-finetune-huggingface-model core Fine-tune any HuggingFace CV / VLM / LLM model on local NVIDIA GPUs inside an NGC PyTorch container. Use when the user wants to fine-tune a HuggingFace model (full or LoRA), train a vision / VLM / LLM model end-to-end, generate a … source
tao-train-oneformer core OneFormer for universal image segmentation. Unifies panoptic, instance, and semantic segmentation with a single architecture using task-conditioned queries. Use when training, evaluating, exporting, quantizing, or running inference for a … source
dynamo-recipe-runner core Select, validate, patch, and deploy existing NVIDIA Dynamo Kubernetes recipes. Use for model/backend/GPU/deployment-mode recipe bring-up; use router-starter for router-only mode work and troubleshoot for broken deployments. source

Source: phuryn/pm-skills

Skill Tier What it adds Upstream
ab-test-analysis core Analyze A/B test results with statistical significance, sample size validation, confidence intervals, and ship/extend/stop recommendations. Use when evaluating experiment results, checking if a test reached significance, interpreting split … source
dummy-dataset core Generate realistic dummy datasets for testing with customizable columns, constraints, and output formats (CSV, JSON, SQL, Python script). Use when creating test data, building mock datasets, or generating sample data for development and … source
sql-queries core Generate SQL queries from natural language descriptions. Supports BigQuery, PostgreSQL, MySQL, and other dialects. Reads database schemas from uploaded diagrams or documentation. Use when writing SQL, building data reports, exploring … source
cohort-analysis adjacent Perform cohort analysis on user engagement data — retention curves, feature adoption trends, and segment-level insights. Use when analyzing user retention by cohort, studying feature adoption over time, investigating churn patterns, or … source
metrics-dashboard adjacent Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan. source
lean-canvas adjacent Generate a Lean Canvas with problem, solution, metrics, cost structure, UVP, unfair advantage, channels, segments, and revenue. Use when exploring a lean startup canvas, testing a business hypothesis, or modeling a new venture. source
north-star-metric adjacent Define a North Star Metric and 3-5 supporting input metrics that form a metrics constellation. Classify the business game (Attention, Transaction, Productivity) and validate against 7 criteria for an effective North Star. Use when choosing … source
product-strategy adjacent Create a comprehensive product strategy using the 9-section Product Strategy Canvas — vision, segments, costs, value propositions, trade-offs, metrics, growth, capabilities, and defensibility. Use when building a product strategy, creating … source
gtm-strategy adjacent Create a go-to-market strategy covering marketing channels, messaging, success metrics, and launch timeline. Use when planning a product launch, creating a GTM plan from scratch, or defining a launch strategy for a new market. source

Source: veniceai/skills

Skill Tier What it adds Upstream
venice-characters adjacent Discover and use Venice public characters (persona-driven system prompts with a bound model). Covers GET /characters (search/filter/sort), /characters/{slug}, /characters/{slug}/reviews, the Character schema, and how to apply a character … source
venice-image-edit adjacent Transform existing images with Venice. Covers POST /image/edit (prompt-driven single-image edit), /image/multi-edit (compose 1-3 images), /image/upscale (2-4x upscale + enhance), and /image/background-remove. Accepts base64, file upload, … source
venice-image-generate adjacent Generate images with Venice. Covers POST /image/generate (Venice-native), POST /images/generations (OpenAI-compatible), GET /image/styles (style presets), request fields (prompt, dimensions, cfg_scale, seed, variants, style_preset, … source
venice-api-overview adjacent High-level map of the Venice.ai API - base URL, authentication modes, endpoint categories, response headers, pricing model, error shape, and versioning. Load this first when starting any Venice integration. source
venice-embeddings adjacent Call POST /embeddings on Venice. Covers request shape (input, model, encoding_format, dimensions, user), OpenAI compatibility, response compression (gzip/br), and practical usage for retrieval, clustering, and RAG. source
venice-api-keys adjacent Manage Venice API keys. Covers GET/POST/PATCH/DELETE /api_keys, GET /api_keys/{id}, GET /api_keys/rate_limits, GET /api_keys/rate_limits/log, the two-step /api_keys/generate_web3_key wallet flow, INFERENCE vs ADMIN key types, and per-key … source
venice-errors adjacent Handle Venice API errors correctly. Covers the StandardError / DetailedError / ContentViolationError / X402InferencePaymentRequired body shapes, every meaningful status code (400, 401, 402, 403, 415, 422, 429, 500, 503, 504), the 402 … source
venice-auth adjacent Authenticate to the Venice API with a Bearer API key or with an x402 / SIWE wallet. Covers header formats, the SIWE message fields, TTL and nonce rules, the venice-x402-client SDK, and how to choose between the two modes. source
venice-responses adjacent Use Venice's Alpha POST /responses endpoint - an OpenAI-compatible Responses API with typed output blocks (reasoning, message, function_call, web_search_call). Covers request shape, streaming, differences from /chat/completions, supported … source