What problem does it solve? AI coding agents waste context window budget by blindly reading large, generated, or vendored files — like a 900KB minified bundle or a node_modules tree — and only discovering the cost after the bytes are already loaded. This Skill answers "what will this read cost, and is it worth it?" before any file is opened. ## Core Features & Use Cases - Pre-read cost estimation: Get per-path estimates of bytes, estimated tokens, classification (source, vendored, minified, lockfile, etc.), and a read/skim/skip verdict for any file or directory. - Directory orientation and ranking: Run a bare scan to see a directory's total cost split into worth-reading vs. noise, or rank the most expensive paths with the top command. - Budget-aware read planning: Pass multiple candidate paths and receive a cheapest-first reading order with a running cumulative token total, so you know where to stop within a fixed budget. - Use Case: Before exploring an unfamiliar repository, run a scan to learn that node_modules and a lockfile account for 80% of the cost, then read only the source files that fit your remaining context budget. ## Quick Start Ask the agent to estimate the token cost of a file or directory with read-budget before reading it, for example by running read-budget path src/index.ts.