long-document-evidence-reader

What problem does it solve?

Long documents contain many pages and sources; this skill provides a structured way to read, search, and cite evidence without overwhelming a single LLM context window.

Core Features & Use Cases

• Long-context loading: Load PDFs and codebases into a ContextStore as chunks with source traceability.
• Evidence retrieval: Use optional BM25 pre-filtering to narrow candidate chunks before analysis.
• REPL-driven reasoning: Interactively inspect and process chunks inside a Python REPL using variables and llm_query() for sub-LLMs.
• Final output with traceability: Produce results via FINAL or FINAL_VAR to ensure reproducible, cit-able answers.
• Reference support: Maintain evidence references and headers for auditability.

Quick Start

Provide a PDF or code repository and ask a question; the skill will load the content, enable iterative querying via REPL, and return a final answer with traceable evidence.