36 KiB
36 KiB
External AI agent skills — ict-test-analyst
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 |
|---|---|---|---|
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 |
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 |
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 |
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 |
mcp-builder |
adjacent | 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 |
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 |
xlsx |
adjacent | Use this skill any time a spreadsheet file is the primary input or output. This means any task where the user wants to: open, read, edit, or fix an existing .xlsx, .xlsm, .xltx, .csv, or .tsv file (e.g., adding columns, computing formulas, … | source |
Source: obra/superpowers
- Repository: https://github.com/obra/superpowers (commit
d884ae0, retrieved 2026-07-14) - License: MIT (c) Jesse Vincent
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
test-driven-development |
core | Use when implementing any feature or bugfix, before writing implementation code | source |
using-git-worktrees |
core | 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 |
systematic-debugging |
adjacent | Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes | source |
executing-plans |
adjacent | Use when you have a written implementation plan to execute in a separate session with review checkpoints | 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 |
subagent-driven-development |
adjacent | Use when executing implementation plans with independent tasks in the current session | source |
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 |
dispatching-parallel-agents |
adjacent | Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies | 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 |
verification-before-completion |
adjacent | Use when about to claim work is complete, fixed, or passing, before committing or creating PRs - requires running verification commands and confirming output before making any success claims; evidence before assertions always | source |
writing-plans |
adjacent | Use when you have a spec or requirements for a multi-step task, before touching code | source |
Source: wshobson/agents
- Repository: https://github.com/wshobson/agents (commit
6fd3247, retrieved 2026-07-14) - License: MIT (c) Seth Hobson
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
bats-testing-patterns |
core | Master Bash Automated Testing System (Bats) for comprehensive shell script testing. Use when writing tests for shell scripts, CI/CD pipelines, or requiring test-driven development of shell utilities. | source |
performance-testing-review-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 |
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 |
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 |
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 |
tdd-workflows-tdd-orchestrator (agent) |
core | Master TDD orchestrator specializing in red-green-refactor discipline, multi-agent workflow coordination, and comprehensive test-driven development practices. Enforces TDD best practices across teams with AI-assisted testing and modern … | source |
api-testing-observability-api-documenter (agent) |
core | Master API documentation with OpenAPI 3.1, AI-powered tools, and modern developer experience practices. Create interactive docs, generate SDKs, and build comprehensive developer portals. Use PROACTIVELY for API documentation or developer … | source |
performance-testing-review-performance-engineer (agent) |
core | Expert performance engineer specializing in modern observability, application optimization, and scalable system performance. Masters OpenTelemetry, distributed tracing, load testing, multi-tier caching, Core Web Vitals, and performance … | source |
sql-optimization-patterns |
core | Master SQL query optimization, indexing strategies, and EXPLAIN analysis to dramatically improve database performance and eliminate slow queries. Use when debugging slow queries, designing database schemas, or optimizing application … | source |
bash-defensive-patterns |
core | Master defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety. | source |
code-documentation-code-reviewer (agent) |
core | Elite code review expert specializing in modern AI-powered code analysis, security vulnerabilities, performance optimization, and production reliability. Masters static analysis tools, security scanning, and configuration review with … | 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 |
Source: cypress-io/ai-toolkit
- Repository: https://github.com/cypress-io/ai-toolkit (commit
9c9038e, retrieved 2026-07-14) - License: MIT
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
cypress-author |
adjacent | Creates, updates, and fixes Cypress tests (E2E/end-to-end and component tests). Use when the user asks to create tests, add tests, write tests, update tests, test this file/component, new spec, or fix a failing or flaky test. Apply even … | source |
cypress-explain |
adjacent | Explains Cypress tests (E2E and component tests), and answers questions about Cypress use and behavior. Use when the user asks to explain how a test works, explain how Cypress works, review or critique a test without writing code. Apply … | source |
cypress-docs |
adjacent | Search and extract Cypress information from official documentation (docs.cypress.io, cypress.io); prefer LLM markdown under /llm/* and refuse unverified API or behavior claims. | source |
Source: google/skills
- Repository: https://github.com/google/skills (commit
b15f327, retrieved 2026-07-14) - License: Apache-2.0
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
bigquery-basics |
core | 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 |
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 |
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 |
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 |
datalineage-bigquery-asset-impact-analysis |
core | 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 |
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 |
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 |
agent-platform-eval-flywheel |
adjacent | 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 |
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 |
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 |
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 |
Source: LambdaTest/agent-skills
- Repository: https://github.com/LambdaTest/agent-skills (commit
54824d6, retrieved 2026-07-14) - License: MIT
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
flutter-testing-skill |
core | Generates Flutter widget tests, integration tests, and golden tests in Dart. Supports local execution and TestMu AI cloud for real device testing. Use when user mentions "Flutter", "widget test", "WidgetTester", "testWidgets", … | source |
capybara-skill |
core | Generates Capybara E2E tests in Ruby with RSpec integration. Acceptance testing DSL for web apps. Use when user mentions "Capybara", "visit", "fill_in", "click_button", "Ruby E2E". Triggers on: "Capybara", "Ruby acceptance test", … | source |
testunit-skill |
core | Generates Test::Unit tests in Ruby. Classic xUnit-style testing with assert methods and test case classes. Use when user mentions "Test::Unit", "assert_equal Ruby", "Ruby test-unit". Triggers on: "Test::Unit", "Ruby test-unit", … | source |
newman-cicd-integration |
core | Generate ready-to-use CI/CD pipeline configurations that install and run Newman for automated API testing. Use this skill whenever the user wants to run Newman in a CI pipeline, integrate Postman collections into automated builds, set up … | source |
reqnroll-skill |
core | Generates production-grade Reqnroll BDD automation scripts for web (Selenium 3/4) and mobile (Appium 2) testing in C#. Supports parallel NUnit execution locally and on TestMu AI cloud. Use when the user asks to write BDD tests, automate … | source |
selenide-skill |
core | Generates Selenide tests in Java. Concise UI testing framework built on Selenium with automatic waits and fluent API. Use when user mentions "Selenide", "$(selector)", "shouldBe(visible)", "Selenide Java". Triggers on: "Selenide", "$() … | source |
behat-skill |
core | Generates Behat BDD tests for PHP with Gherkin feature files and MinkContext for browser testing. Use when user mentions "Behat", "PHP BDD", "Mink", "behat.yml". Triggers on: "Behat", "PHP BDD", "Mink", "behat.yml", "FeatureContext PHP". | source |
cicd-pipeline-skill |
core | Generates CI/CD pipeline configurations for test automation with GitHub Actions, Jenkins, GitLab CI, and Azure DevOps. Includes TestMu AI cloud integration. Use when user mentions "CI/CD", "pipeline", "GitHub Actions", "Jenkins", "GitLab … | source |
codeception-skill |
core | Generates Codeception tests in PHP covering acceptance, functional, and unit testing. BDD-style with Actor pattern. Use when user mentions "Codeception", "$I->amOnPage", "$I->see", "Cest". Triggers on: "Codeception", "$I->amOnPage", … | source |
jest-skill |
core | Generates Jest unit and integration tests in JavaScript or TypeScript. Covers mocking, snapshots, async testing, and React component testing. Use when user mentions "Jest", "describe/it/expect", "jest.mock", "toMatchSnapshot". Triggers on: … | source |
xcuitest-skill |
core | Generates XCUITest UI tests for iOS/iPadOS apps in Swift. Apple's native testing framework for reliable, fast UI automation. Supports local simulators and TestMu AI cloud real devices. Use when user mentions "XCUITest", "XCTest", "iOS UI … | source |
appium-skill |
core | Generates production-grade Appium mobile automation scripts for Android and iOS in Java, Python, or JavaScript. Supports real device and emulator testing locally and on TestMu AI cloud with 100+ real devices. Use when the user asks to … | source |
Source: czlonkowski/n8n-skills
- Repository: https://github.com/czlonkowski/n8n-skills (commit
9ea3aa5, retrieved 2026-07-14) - License: MIT
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
n8n-validation-expert |
core | 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 |
using-n8n-mcp-skills |
adjacent | Use when building, editing, validating, testing, or debugging an n8n workflow through the n8n-mcp MCP server — designing a flow, configuring a node, writing an expression or Code node, wiring credentials, or fixing one that misbehaves. The … | 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-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-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-self-hosting |
adjacent | Deploy a production self-hosted n8n end-to-end to a fresh Linux VM over SSH, using Docker Compose behind a Caddy reverse proxy with automatic HTTPS. Use whenever the user wants to self-host, install, set up, provision, or deploy n8n on … | 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-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-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-code-python |
adjacent | 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 |
adjacent | 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 |
Source: NVIDIA/skills
- Repository: https://github.com/NVIDIA/skills (commit
153b14b, retrieved 2026-07-14) - License: CC-BY-4.0 (skills/docs), Apache-2.0 (code)
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
hsb-app |
core | Discover and run Holoscan Sensor Bridge example applications on a connected devkit. Filters available apps by the user's platform, HSB software version, board type, and sensors. Supports timed execution, failure analysis, code-edit … | source |
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 |
dali-dynamic-mode |
core | DALI imperative dynamic mode (nvidia.dali.experimental.dynamic, ndd): use when working on ndd code or migrating pipelines; skip pipeline-only tasks. |
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 |
vss-generate-video-report |
core | Use this skill when producing a VSS analysis report — Mode A per-clip VLM, Mode B incident-range via video-analytics. Not for standalone video summarization, real-time alerts or ad-hoc Q&A. | source |
mcore-create-issue |
core | Investigate a failing GitHub Actions run or job and create a GitHub issue for the failure. | source |
nemo-rl-docs |
adjacent | Documentation conventions for NeMo-RL. Covers docs/index.md updates and docstring format. Do NOT use for: bug fixes, test fixes, dependency bumps, refactoring, CI/CD changes, performance tuning, or any task that does not involve writing or … | source |
digital-health-clinical-asr-setup |
adjacent | Stage 1 of Clinical ASR Flywheel. Use when bootstrapping a cycle: NVCF+MW disclosure, NVIDIA_API_KEY check, deps install, TTS+ASR smoke test. | source |
cuopt-developer |
adjacent | Modify, build, test, debug, and contribute to NVIDIA cuOpt (C++/CUDA, Python, server, CI). Use for solver internals, PRs, DCO, and code conventions. | source |
amc-setup-calibration-stack |
adjacent | Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API … | source |
cuopt-numerical-optimization-api |
adjacent | LP, MILP, and QP (beta) with cuOpt — Python, C, and CLI. Use when the user is solving LP, MILP, or QP with any cuOpt interface. | source |
cuopt-numerical-optimization-formulation |
adjacent | LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). Concepts only; no API. | source |
Source: phuryn/pm-skills
- Repository: https://github.com/phuryn/pm-skills (commit
18468a9, retrieved 2026-07-14) - License: MIT
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
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 |
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 |
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 |
core | 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 |
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 |
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 |
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 |
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 |
Source: veniceai/skills
- Repository: https://github.com/veniceai/skills (commit
de089fa, retrieved 2026-07-14) - License: MIT
| Skill | Tier | What it adds | Upstream |
|---|---|---|---|
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-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-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-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-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 |