Synaptic FAQs

Question 1

What are the benefits of using Synaptic with AI agents or LLMs?

Accepted Answer

Synaptic enables AI agents to query a compact, optimized code graph instead of raw files. This 'token economy' significantly reduces the number of tokens required (up to 30x fewer), allowing AI assistants to quickly and accurately answer structural questions, forecast changes, and generate code with higher confidence and lower cost.

Question 2

What is Synaptic and how does it help developers?

Accepted Answer

Synaptic converts any codebase into a queryable knowledge graph, providing deep structural clarity. It helps developers understand dependencies, predict the impact of changes, plan safe refactors, and verify code integrity before execution, saving time and preventing errors.

Question 3

What programming languages does Synaptic support?

Accepted Answer

Synaptic supports over 30 programming languages through tree-sitter, along with regex-based extractors for various formats and script extraction for frameworks like Vue, Svelte, and Astro, ensuring broad compatibility across diverse tech stacks.

Question 4

How does Synaptic facilitate safe refactoring?

Accepted Answer

Synaptic offers 'safe refactor' commands (rename, move, extract) that generate a confidence-scored execution plan. It then verifies the refactor by rebuilding and checking the graph, ensuring no references are lost, and no new cycles are introduced, all without directly editing source code.

Question 5

Can Synaptic help with SQL performance and security?

Accepted Answer

Yes, Synaptic includes robust SQL auditing capabilities. It flags potential issues like SQL injection, missing indexes, N+1 patterns, over-broad grants, and row-level security gaps. It can also advise on candidate SQL queries against your existing database schema and application code.

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