CODYNEX Engine
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- AlicenseNot gradedqualityBmaintenanceGives coding agents local software intelligence: it surfaces the files, tests, and helpers relevant to a task before edits, flags missed callers and uncovered code during review, and returns a single SHIP / NOT PROVEN / NO-SHIP verdict when the agent stops. Everything runs on the local index with no network calls, so repository code stays on the machine.3,833 npm10MIT
- AlicenseNot gradedqualityAmaintenanceEnables AI coding agents to query a local structural code graph, inspect relationships and impact, and retrieve focused project context before reading full files.28 npmMIT
- AlicenseNot gradedqualityDmaintenanceLive codebase intelligence for AI agents. Import graph PageRank for file importance, git forensics for co-change coupling and fragile code, convention detection across 16 domains, and blast radius analysis.21 npm3Business Source 1.1
- AlicenseBqualityBmaintenanceIndexes a Python/JS/TS repository into a local SQLite knowledge graph so agents can trace callers, callees, imports, subclasses and covering tests, measure impact radius, rank diff risk, and summarize architecture without grepping files. Exposes these queries as MCP tools alongside an equivalent CLI, with no daemon, embeddings, or network access.10MIT
- AlicenseBqualityBmaintenanceEnables AI agents to index local Python repositories and retrieve code intelligence through semantic search, caller lookups, hybrid context expansion, and visualization.5MIT
- AlicenseNot gradedqualityCmaintenanceEnables AI coding agents and developers to search code by meaning and exact text, map symbols, dependencies, blast radius and context, inspect git-change impacts, and trace live Python or JavaScript execution from a local air-gapped SQLite index.Apache 2.0
TDQS
Scored across 4 tools
Each tool targets a distinct capability: architecture summary, component impact, historical decisions, and request-level change planning. No two tools overlap in input or output scope, so an agent can easily select the right one.
All four tools use the dna_ prefix followed by a single noun (map, impact, decisions, plan), forming a consistent and predictable naming convention.
Four tools are well-suited for a focused architecture analysis engine; each covers a unique analysis dimension without redundancy.
The set covers key analysis outputs (summary, impact, decisions, plan) but lacks a tool to ingest/refresh the project or drill into specific components/decisions, leaving minor workflow gaps.