the apiary 
How does nectar compare to coderag? Same goal, opposite grain. coderag chops your code into function chunks and embeds each one. nectar describes whole files, one plain-language description each. Finer is not always better, and nectar makes a deliberate different bet. Close in aim, not competition.
coderag stands in for a large family of tools that parse your code into an abstract syntax tree, split it into chunks at the function and class level, embed every chunk, and expose semantic search over a vector database. It watches for changes and reindexes incrementally. It is a mature, capable pattern, and it gives fine-grained recall: a specific function within a file.
| nectar | coderag | |
|---|---|---|
| what gets described | yes. whole files one description each | partial. code chunks many per file |
| entries per file | yes. one | partial. dozens |
| what it can index | yes. any text file config, markdown, env | partial. parseable code |
| stable identity | yes. yes survives moves | no. no keyed by a db row |
| store | honeycomb advantage. a store you own exact plus meaning | partial. a vector database |
| symbol-level precision | partial. via the code graph | honeycomb advantage. yes coderag's real strength |
Capability comparison, not a benchmark. From the public materials of the chunk-and-embed family and our survey, captured 2026-06.
nectar's bet is that "what is this file for" is the useful question most of the time, that it works on files a parser cannot read, and that it keeps entry counts far lower. Symbol-level precision is real, and nectar leaves it to the structural code graph that already ships in the stack rather than duplicating it. A future nectar could add symbol-level descriptions if file-level proves too coarse.
See how nectar worksA family of tools that parse code into an AST, split it into function and class chunks, embed every chunk, and search over a vector database. It gives fine-grained, function-level recall.
Because what is this file for is the useful case most of the time, it works on files a parser cannot read, and it keeps entry counts far lower. Symbol-level precision is handled by the code graph in the stack.
For fine-grained, function-level search when your codebase is all in parser-friendly languages. Pick nectar for file-level understanding across every text file, identity that survives refactors, and recall fused with your memory.
nectar describes whole files and survives refactors. Install it with the rest of the stack.
Windows (PowerShell): irm https://get.theapiary.sh/install.ps1 | iex
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