io.github.KoyoYeager/pystub
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- FlicenseAqualityBmaintenanceEnables local-first AST-based code context pruning for LLMs and AI coding agents, stripping internal function bodies to stubs while preserving signatures, interfaces, type hints, and docstrings to reduce token usage.3-
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- FlicenseNot gradedqualityNot gradedmaintenanceEnables developers and coding agents to refactor Python codebases by re-aliasing imports and migrating dependencies, safely rewriting module paths and callsites through deterministic AST analysis instead of error-prone regex. It also surfaces dependency graphs and refactoring plans that minimize LLM token usage.-
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: analyze classifies packages, check dives into specific usage, generate produces stubs, generate_submodule handles C extension submodules, and graph visualizes imports. No overlap.
All tool names follow a consistent pattern: lowercase English verbs (analyze, check, generate, graph) with one compound (generate_submodule) that follows the verb_noun convention. No mixing of styles.
5 tools is well-scoped for the domain of import analysis and stub generation, covering detection, inspection, generation (both regular and submodule), and visualization without unnecessary tools.
The tool set covers the core workflow: detection, detailed analysis, stub generation for both regular and C extension packages, and visualization. Missing a tool to actually write stubs to disk or apply them, but this can be done externally.