Synapses FAQs

Question 1

What programming languages does Synapses support for parsing?

Accepted Answer

Synapses provides deep Abstract Syntax Tree (AST) parsing for 18 major languages, including Go, TypeScript, Python, Java, C++, Rust, C#, PHP, Ruby, and more. It also offers file-level tracking for over 80 additional languages, ensuring broad compatibility.

Question 2

What is Synapses and how does it enhance AI coding agents?

Accepted Answer

Synapses is a local-first, graph-based context manager that provides AI coding agents with structurally precise code subgraphs. Instead of generic code dumps, agents receive only the mathematically-carved nodes and edges they truly need, enabling deep code intelligence and preventing hallucination.

Question 3

How does Synapses manage agent tasks and context across multiple LLM sessions?

Accepted Answer

Synapses features 'Agent Task Memory' tools. Agents can use `create_plan`, `get_pending_tasks`, and `update_task` to store and manage their work, plans, and task statuses. This ensures continuity and allows agents to pick up exactly where they left off across different LLM conversations.

Question 4

How does Synapses' 'Context Carving' work?

Accepted Answer

Context Carving uses a BFS ego-graph algorithm with relevance decay. When an agent requests context for an entity, Synapses expands outward a specified number of hops, sorts nodes by relevance (based on edge weights and distance), and prunes the result to fit within a token budget. This delivers a highly relevant, compact subgraph.

Question 5

Can Synapses help enforce code architecture and quality?

Accepted Answer

Yes, Synapses includes 'Architectural Rules' that allow you to define and enforce code structure constraints. These rules, configurable via `synapses.json` or dynamic runtime updates, help maintain code quality and can even validate proposed code changes against defined standards.

Synapses

Synapses

Características Principales

Casos de Uso

Características Principales

Casos de Uso