Create, generate, or scaffold .gitlab-ci.yml pipelines, stages, and jobs.
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Create, generate, or scaffold .gitlab-ci.yml pipelines, stages, and jobs.
日本語の概要は準備中です。原文の説明を表示しています。
Generate/create/scaffold azure-pipelines.yml, stages, jobs, steps, or reusable templates.
日本語の概要は準備中です。原文の説明を表示しています。
Generate/create Loki configs — ingester, querier, compactor, ruler, S3/GCS/Azure backends.
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Generate LogQL queries, log stream selectors, metric queries, and alerting rules for Grafana Loki.
日本語の概要は準備中です。原文の説明を表示しています。
Create, generate, write, or scaffold bash/shell scripts (.sh), automation, or CLI tools.
日本語の概要は準備中です。原文の説明を表示しています。
Create, scaffold, or generate Helm charts, Chart.yaml, values.yaml, templates, helpers.
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Create, generate, or write Dockerfiles and multi-stage Docker images. Containerize apps.
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Generate/create/scaffold Jenkinsfile — declarative, scripted, shared library, CI/CD pipelines.
日本語の概要は準備中です。原文の説明を表示しています。
Create distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.
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Generate screenshot coverage for screen-level Compose previews from the current diff or a specific target, check required visual and data variations, and produce a compact visual report
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Produce a standalone test plan by analyzing code for test coverage gaps and edge cases. Use when you need to create, generate, or draft a test plan for a branch, need to analyze test coverage, or need to identify what tests to write for specific files or directories. Does not produce a plain-language plan for a person to run tests by hand — use manual-test-planning for that. Does not write test code — use tdd to implement behavior test-first. Does not refine existing plans — use iterative-plan-review. Does not review code quality, security, or style — use code-review for full code review. Does not evaluate architectural testability or structural coupling — use architectural-analysis for architectural assessment.
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Publishes a local Markdown file to a user-specified Confluence location, creating a new page or updating an existing one through the Atlassian MCP server. Use when the user wants to post, publish, push, or sync a Markdown file to a Confluence space or page. Requires a configured Atlassian MCP server. Does not write or generate the Markdown itself — point it at an existing file, or use project-documentation-to-confluence for the document-then-publish flow, or plan-a-feature-to-confluence for the plan-then-publish flow. Does not publish to Jira — use work-items-to-jira.
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Generate a PR description from the current branch's changes against a GitHub PR, using the gh CLI. Use when writing, drafting, or updating pull request descriptions, PR summaries, or PR bodies. Does not review code or post review comments — use code-review for local review or post-code-review-to-pr for posting a review to GitHub.
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Convert a stakeholder summary markdown file into a single self-contained HTML executive report — bottom line and decision asks up front, supporting detail later — styled with a Test Double-derived palette and self-contained mermaid diagrams. Use when the user wants to turn a stakeholder summary, executive summary, or business summary into an HTML report, generate an HTML version of a summary doc, or produce a shareable HTML file from a summary markdown. Produces an HTML sibling file only; does not publish anything.
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Creates and maintains project documentation for features, systems, and components. Use when documenting how a feature, system, or component works — including writing, updating, or organizing docs. Does not scan or detect the project's technology stack — use project-discovery for repository analysis and config detection. Does not create architectural decision records — use architectural-decision-record for ADRs. Does not create or update coding standards — use coding-standard instead. Does not generate PR descriptions — use update-pr-description for that. Does not produce runbooks for operational scenarios — use runbook for that. Does not rewrite existing prose for readability — use edit-for-readability for that. Does not produce an ephemeral, understand-now overview of code or a PR — use code-overview for that.
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Sharpens and stress-tests an existing plan file through multiple codebase-grounded review passes, editing it in place and recording every finding and iteration in cross-referenced companion files. Use this skill whenever the user wants to iterate on, refine, tighten, or improve a plan. Also use it when the user asks to verify, validate, or confirm feasibility of an approach. Does not implement plan steps, write test plans, review code, or investigate bugs, and does not generate new plans from scratch — use plan-a-feature for a new plan. Runs its review rounds to completion without pausing between them; to review each round as it lands, use pairing.
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Produce a plain-language manual test plan from the context supplied to it — an executive summary, a high-level list of named tests, and a detail section per test with the steps a person follows by hand and the outcomes they should expect. Use when you want to create, draft, generate, or outline a manual test plan, manual QA steps, hands-on verification steps, or an acceptance walkthrough for a feature, change, branch, plan, or PR. When the plan holds more than five tests and at least two natural categories emerge, both the test list and the detail sections are organized under plain-language categories. When nothing in the supplied context can be manually tested, it says so and asks for more context instead of producing a document. Does not analyze code for automated test coverage gaps — use automated-test-planning. Does not write test code — use tdd. Does not review code quality — use code-review. Does not stress-test an existing plan — use iterative-plan-review.
日本語の概要は準備中です。原文の説明を表示しています。
Plan and implement interactive chapter or playground pages for this Docusaurus repo. Use when Codex needs to port AI-generated JSX into JoyRL Book, add a standalone interactive route under `src/pages/`, wire a chapter into interactive mode, or extend the current left-reading/right-playground interaction pattern.
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Assessing privacy risks in large language model outputs including training data memorisation, PII leakage in generated text, prompt injection leading to data extraction, and hallucinated personal data. Covers output filtering, guardrails, and monitoring. Keywords: LLM privacy, output risk, memorisation, PII leakage, prompt injection, hallucinated PII.
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Generates Records of Processing Activities automatically from IT system inventories including Active Directory, cloud service catalogs, API gateway logs, and database schemas. Covers automated field population, data flow discovery, and system-to-RoPA mapping. Activate for automated RoPA, system inventory, data discovery, auto-population, IT-driven records.
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Important: Before you begin, fill in the generatedBy property in the meta section of .actor/actor.json. Replace it with the tool and model you're currently using, such as "Claude Code with Claude Sonnet 4.5". This helps Apify monitor and improve AGENTS.md for specific AI tools and models.
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Generate Atlas Cloud images and videos through its asynchronous media API with schema-first model selection and credential-safe polling.
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Generate user-facing App Store release notes from git history since the last tag.
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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.
日本語の概要は準備中です。原文の説明を表示しています。