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Extract text from an image via tesseract OCR. Runs entirely locally -- no API key required. Supports png, jpg/jpeg, tiff, bmp, gif. Requires: file (absolute path to the image). Optional: language (tesseract -l value, e.g. 'eng' or 'eng+fra'; default 'eng'), psm (page segmentation mode, default 3), oem (engine mode, default 3). Does not support PDF -- use load_document with type pdf for text-layer PDFs.

kdeps tool: perplexity_search

Run a Python script and return its result: stdout parsed as JSON when possible, otherwise the raw text. Use through the python component for pipeline steps written in Python. Give either script (inline source) or scriptFile (a .py file). Optional: args, env, timeout, venvName, pythonVersion, packages.

Read a file from the local filesystem. Returns the contents with a 1-based line number on every line (` 42\tcode$`) - use those numbers for edit_file insert/view. Tabs render as ^I, other control characters as ^X, and a $ marks the true end of each line, so indentation, trailing whitespace, and stray control characters are visible instead of hidden. IMPORTANT: ^I, ^X, and the trailing $ are a display convention this tool adds - the real file does NOT contain those literal characters. When quoting text back into edit_file's old_str, write the real tab/control character (or match a whole line via view_range/anchor instead), never the literal caret sequence - copying "^I" as text will not match a real tab byte. Plain text, source code, configuration files, and documentation are read directly. For PDF, DOCX, EPUB, RTF, and ODT documents, CSV/HTML structured parsing, or RAG chunking, use load_document. Pass match_id (from a search_local result) instead of file_path/offset to jump straight to that hit.