Guide for building RAG (retrieval-augmented generation) chatbots and Q&A systems with Elasticsearch. Use when a developer wants to build a chatbot, Q&A system, or AI assistant that answers questions from their own data.
Encrypted Saved Objects (ESO) in Kibana — registration, AAD attribute choices, partial update safety, model version migrations with createModelVersion, canEncrypt checks, and Serverless constraints. Use when creating, modifying, or working with ESO types.
Generate or repair a Scout test scaffold for a Kibana plugin/package (test/scout*/{api,ui} Playwright configs, fixtures, example specs). Use when you need the initial Scout directory structure; prefer `node scripts/scout.js generate` with flags for non-interactive/LLM execution.
Fetch and analyse Buildkite CI logs for the elastic/kibana repo. Provides helpers to retrieve build/job logs by build number or PR number, summarise failures, and inspect artifacts. Use when the user asks about CI failures, Buildkite logs, a failing build, a red CI, build artifacts, or mentions a Buildkite URL or PR number in the context of CI.
Fix API documentation issues in a Kibana plugin or package. Use when asked to fix, improve, or add JSDoc/API documentation for a Kibana plugin or package, or when check_package_docs validation fails.
Write LLM evaluation spec files with datasets, tasks, and evaluators using the @kbn/evals Playwright fixture. Use when authoring new eval specs, adding datasets or evaluators, or debugging evaluation test failures.
CSS and UI animation patterns for responsive, polished interfaces. Use when implementing hover effects, tooltips, button feedback, transitions, or fixing animation issues like flicker and shakiness.
Workflows and commands for managing Alembic database migrations and schema changes in the letta-cloud core app, including using uv, just, LETTA_PG_URI, and switching between SQLite and Postgres.
Run an anti-slop cleanup/refactor/deslop workflow
Analyze main branch implementation and configuration to find missing, incorrect, or outdated documentation in docs/. Use when asked to audit doc coverage, sync docs with code, or propose doc updates/structure changes. Only update English docs under docs/** and never touch translated docs under docs/ja, docs/ko, or docs/zh. Provide a report and ask for approval before editing docs.
Analyze CSV files in /mnt/data and return concise numeric summaries.
Run python examples in auto mode with logging, rerun helpers, and background control.
Perform a release-readiness review by locating the previous release tag from remote tags and auditing the diff (e.g., v1.2.3...<commit>) for breaking changes, regressions, improvement opportunities, and risks before releasing openai-agents-python.
Create the required PR-ready summary block, branch suggestion, title, and draft description for openai-agents-python. Use in the final handoff after moderate-or-larger changes to runtime code, tests, examples, build/test configuration, or docs with behavior impact; skip only for trivial or conversation-only tasks, repo-meta/doc-only tasks without behavior impact, or when the user explicitly says not to include the PR draft block.
Use when working with the OpenAI API (Responses API) or OpenAI platform features (tools, streaming, Realtime API, auth, models, rate limits, MCP) and you need authoritative, up-to-date documentation (schemas, examples, limits, edge cases). Prefer the OpenAI Developer Documentation MCP server tools when available; otherwise guide the user to enable `openaiDeveloperDocs`.
Run the mandatory verification stack when changes affect runtime code, tests, or build/test behavior in the OpenAI Agents Python repository.
Improve test coverage in the OpenAI Agents Python repository: run `make coverage`, inspect coverage artifacts, identify low-coverage files, propose high-impact tests, and confirm with the user before writing tests.
