claude-skills

Advanced python-docx patterns for handling nested tables, complex cell structures, and content extraction beyond basic .text property. Complements the official docx skill with specialized techniques for forms, checklists, and complex layouts.

Extract PDFs to text and images before reading

Implement RLM-style (Recursive Language Model) orchestration for complex tasks. This skill should be used when facing large context requirements, multi-part tasks that would benefit from parallel execution, or when context rot is a concern. Automatically decomposes tasks, spawns parallel subagents, aggregates results, and iterates until completion. Inspired by the RLM research paper (arXiv:2512.24601).

Advanced python-docx patterns for nested tables, complex cells, and content extraction beyond .text property. Techniques for forms, checklists, and complex layouts.

Fill DOCX template forms programmatically while preserving 100% of original structure - logos, footers, styles, metadata. Zero-artifact insertion for forms, applications, and standardized documents. Output indistinguishable from manual filling.

Use when adding/editing/querying content in an existing Obsidian vault, configuring plugins, integrating Claude Code with Obsidian via Local REST API or CLI, automating ongoing capture/organization/retrieval, designing a personal knowledge management workflow, OR building academic study vaults (course prep, exam-ready, mock-exam content — the durable academic-study patterns from a deprecated companion skill have been folded into this one).

Use when creating or editing documents (DOCX, PDF, XLSX, PPTX) that need professional output. Adds visual verification, typography hygiene, and formula patterns to the document-skills plugin.

Use when a project needs multi-session retrospective analysis: after milestones, before starting a new phase, when vision drift is suspected, or every 3-5 sessions. Triggers include user saying retro, run a retro, since-last-retro; asks to analyze patterns, recurring mistakes, or correction trends across multiple sessions; says how did we get here or project history in a project-arc context (not single-file diffs or README edits); or notes that MEMORY.md has drifted from what actually happened across sessions. NOT for single-session review, MEMORY.md cleanup, retro templates, or git-level file diffs.

Activate autonomous Ralph Wiggum loop mode for iterative task completion. Use when you have a well-defined task with clear completion criteria that benefits from persistent, autonomous execution.

Translate structured documents (DOCX) to RTL languages (Arabic, Hebrew, Urdu) while preserving exact formatting, table structures, colors, and layouts. Handles quote normalization, multi-pass translation matching, and RTL-specific formatting patterns.

Use when brainstorming a product or feature where multiple valid technology choices exist and the wrong one is costly, when the user asks for 'objectively best' or 'highest quality', or when the domain has tools/frameworks where marketing or popularity biases could mislead research agents. Also use when starting architecture decisions, evaluating tech stacks, or when the user mentions bias, vendor lock-in, hallucinated benchmarks, or wants research-backed decisions rather than default recommendations.

Use when creating or editing documents (DOCX, PDF, XLSX, PPTX) that need professional output. Adds visual verification, typography hygiene, and formula patterns.

Fill DOCX template forms preserving 100% original structure - logos, footers, styles, metadata. Zero-artifact insertion. Output indistinguishable from manual entry.

Translate DOCX to RTL languages (Arabic, Hebrew, Urdu) preserving exact formatting, tables, colors, layouts. Handles quote normalization and multi-pass matching.