run-llama

Invoke this skill BEFORE implementing any text extraction/parsing logic to learn how to use LlamaParse to process any document accurately. Requires llama_cloud_services package and LLAMA_CLOUD_API_KEY as an environment variable.

Invoke this skill BEFORE implementing any structured data extraction from documents to learn the correct llama_cloud_services API usage. Required reading before writing extraction code. Requires llama_cloud_services package and LLAMA_CLOUD_API_KEY as an environment variable.

Invoke this skill BEFORE implementing any text/document classification task to learn the correct llama_cloud_services API usage. Required reading before writing classification code." Requires the llama_cloud_services package and LLAMA_CLOUD_API_KEY as an environment variable.

Leverage Retrieval Augmented Generation to retrieve relevant information from a a LlamaCloud Index. Requires the llama_cloud_services package and LLAMA_CLOUD_API_KEY as an environment variable.

Use llamactl to initialize, locally preview, deploy and manage LlamaIndex workflows as LlamaAgents. Required llama-index-workflows and llamactl to be installed in the environment.

Use this skill whenever a question should be answered from documents stored in a LlamaCloud Index v2 knowledge base — retrieving passages, locating indexed files, or searching indexed content through the LlamaParse Platform REST API with curl. Teaches agentic retrieval — navigating an index like a file system instead of one-shot RAG.

Use this skill whenever a task involves a document file (PDF, DOCX, PPTX, XLSX, or image) and you need to read it or pull text, tables, or specific values out of it — to answer a question about its contents, look up a figure, or extract data. Provides fast, local, model-free extraction via the `lit` CLI with disciplined, low-cost search patterns.

Use this skill when the user asks to parse the content of an unstructured file (PDF, PPTX, DOCX...)

Diagnose problems with an installed LlamaCloud release — pods crashing, services not reachable, login broken, parses failing, OCR queue stuck, etc. Use when the user says "something's wrong", "pods are stuck", "X is failing", "the install came up but something is broken", or pastes a kubectl error. Performs a structured symptom-to-cause walk using read-only kubectl and cloud CLI commands, then matches against the LlamaCloud-specific pattern library in `patterns.md`. Produces a `debug-report.md` safe to share with LlamaIndex support.

Run `helm install` (or `helm upgrade --install`) for the LlamaCloud chart, monitor the rollout in real time, surface failing pods immediately, and capture a diagnostic bundle if anything fails. Use when the user says "install the chart", "run helm install", "deploy llamacloud", "upgrade", or naturally follows a successful preinstall-check. Runs with `--wait --timeout` and intentionally **does not** pass `--atomic`, so failed pods remain in place for the `debug` skill to investigate. Read-only against the cluster except for the helm install itself.

Validate a values.yaml and verify cluster + dependency reachability before running `helm install` for the LlamaCloud chart. Use when the user says "preinstall check", "validate my values", "check before install", "preflight", or before any first-time install or upgrade. Performs static schema validation, cluster capacity inspection, local network probes, and read-only routing checks against managed cloud services (AWS / Azure / GCP). Fully read-only by default; only one optional phase can create a short-lived Job, and only with explicit user consent.

Use this skill whenever a question should be answered from documents stored in a LlamaCloud Index v2 knowledge base — retrieving passages, locating indexed files, or searching indexed content through the LlamaParse MCP Index v2 tools (retrieveFromIndex, findFilesInIndex, grepFileFromIndex...). Teaches agentic retrieval — navigating an index like a file system instead of one-shot RAG.

Skill on how to use the LlamaParse MCP tools

Use this skill when the user asks to parse the content of an unstructured file (PDF, PPTX, DOCX...)

Use this skill when the user asks to parse, perform multi-format document conversion or spatially extract text from an unstructured file (PDF, DOCX, PPTX, XLSX, images, etc.) locally without cloud dependencies.

Use this skill whenever a task involves a document file (PDF, DOCX, PPTX, XLSX, or image) and you need to read it or get text, tables, or specific values out of it — including to answer a question about its contents, look up a figure, extract data, or convert it to text/JSON. Provides fast, local, model-free extraction with no cloud or API key. Reach for this instead of ad-hoc pdftotext/pypdf/textract whenever a question or task references a document file.

Plan and run a design-QA / "taste test" of llamactl changes against a real backend. Cooperatively builds a small matrix of cases worth eyeballing, runs them against a chosen backend (test environment by default, local kind+tilt for new API contract changes), and writes a design-review report to `thoughts/shared/qa/`. Use this for changes to `llamactl` commands, output formats, auth, or control-plane API contracts. For UI/template smoke tests, use `llamactl_browser_test` instead.

Skill on how to use the LlamaParse MCP tools