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CAD for code.

Deterministic search & edit tools for coding agents — delivered via MCP.

rename 'execute' Verified
The Limitation

Today's tools are fast, flexible, and great at finding text.

But code isn't text.

It has structure, syntax, relationships, and meaning.
Text tools see none of it — so agents loop, re-check, and hope it compiles.

Code is Data.

The Approach

pandō builds a map of your code — giving agents the ability to search and edit by meaning, not just text.

Imagine a 1,000-page novel. Your protagonist is George. Halfway through, you decide he's now Camellia.
You need to update every reference — and change nothing else.

George Camellia
Direct Reference

Trivial find & replace. Both tools get it right.

Pronoun Reference

Which one is George and which Alpha?

Aliased Reference

Did we catch all relations, like friend or coworker?

The Guarantee

Structure, not Strings.

pandō is

Exact

This gives you

Correct Syntax

Code generated by the agent is syntactically valid (compiler-checked before commit)

Deterministic AST

Transformations validate against the Abstract Syntax Tree before commit.

# Rename UserService → AuthService
 
rename UserService AuthService
indexing symbol graph...
47 references across 12 files
running compiler preflight...
preflight passed
 
done 0 syntax errors · 0 collateral changes
pandō is

Safer

This gives you

Semantic Undo

Every edit gets a snapshot. Rollback from anything.

Atomic Transactions

Edits apply atomically. Either the whole graph updates, or nothing does.

# Atomic rename with rollback
 
rename db database
snapshot S_20260223_091541 created
updated 23 true references
skipped 4 string literals (intentional)
skipped 2 comments (intentional)
 
applied atomically rollback available
pandō is

Faster

This gives you

10–100×

Text tools require LLM verification for every match. pandō edits the reference graph directly. No uploads, no inference.

Local Execution

pandō talks to your local disk, not the LLM. Most searches take milliseconds — just a database query.

# Rename across large monorepo
 
rename processPayment handlePayment
symbol lookup 0.3ms (local index)
references found 785 across 171 files
network calls 0
applying changes...
 
done in 14.2s all local
text-tool equivalent: ~25 min (785 LLM round-trips)
pandō is

Leaner

This gives you

Token Savings

Achieves >100× token compression for some operations (e.g. rename costs the same for one or a thousand references)

O(n) → O(1) Cost

Token cost is O(n) (n = references) using text tools (for some ops). pandō is O(1): just the operation params + symbol name.

# Token cost: rename across 64 files
 
text tools (search & replace via LLM):
files sent to model 64
avg tokens / file ~800
total ~51,200 tokens O(n)
 
pandō:
tokens used ~40 O(1) — same for 1 or 1,000 refs
 
1,280× fewer tokens cost scales with intent, not codebase
pandō is

Tighter

This gives you

Reduced Exposure

Some operations send no code at all to the LLM — just the intent of the transform.

Scalable Codemods

Operations like FMR require O(1) input, generate O(1) output, and modify arbitrary code volume.

# FMR: add structured logging
 
fmr Logger.info(*) Logger.info(*, {structured: true})
scanning AST nodes...
312 matches across 89 files
bytes sent to model 0
applying changes...
 
done in 2.1s 312 replacements · 0 bytes exposed
Supported: TypeScript · JavaScript · Python · C# · C/C++ Expanding to: Java, Rust, Go, Clojure, Perl

Vibe Freely.
Architect Precisely.

Free VS Code extension. One install, zero config — runs alongside your stack.

Free for personal use · Organization at $999/year/dev