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Show HN: DeltaCode – Pure AST beat Qwen's zvec-grep on our test (92% vs 48%)

DeltaCode, an open-source coding-agent tool from aitrailblazer, reports that its deterministic AST-based ranker achieved 92% path Recall@5 on a frozen 25-case private Go-repository suite, outperforming two zvec-grep model configurations that reached 40% and 48% on their best routes. Version 0.1 uses no vector database, embeddings, or network access, and the results are not independently reproducible because the repository and tasks are private.

read3 min views1 publishedSep 3, 2026
Show HN: DeltaCode – Pure AST beat Qwen's zvec-grep on our test (92% vs 48%)
Image: Michielbdejong (auto-discovered)

Deterministic task-to-symbol discovery and bounded AST context for coding agents.

DeltaCode turns a coding objective into a small, inspectable context packet. It uses repository paths, Go symbols, signatures, receivers, comments, and function bodies—not embeddings—to rank likely implementation sites. It then returns bounded Go or Python AST slices with source hashes.

Version 0.1 deliberately has:

  • no vector database;
  • no embedding model or model download;
  • no persistent index or indexing daemon;
  • no network access in discovery and slicing;
  • no code-execution authority.

The MCP transport uses the official Go MCP SDK. The retrieval and slicing core uses the Go standard library.

On one frozen 25-case private Go-repository suite, the structural ranker reached 92% path Recall@5. The two tested zvec-grep

model configurations reached 40% and 48% on their best routes. That is a result for one repository and one frozen task set—not a universal claim that AST retrieval beats vector retrieval.

The underlying repository and task definitions are private, so this historical result is not independently reproducible. A cross-repository public benchmark is required before broader comparative claims.

Frozen private suite (25 cases) Recall@1 Recall@5 Exact symbol@5 p95
DeltaCode structural ranker, current replay 72% 92%
80%
169 ms
zvec-grep + Jina, vector route
8% 48% 0% 401 ms
zvec-grep + Potion, best path route
8% 40% 16% 687 ms

The aggregate receipt and its limitations are in benchmarks/private-go-summary.json.

go install github.com/aitrailblazer/deltacode-engine/cmd/deltacode@v0.1.0

go test ./...
go build -trimpath -o ./bin/deltacode ./cmd/deltacode
./bin/deltacode discover \
  -root /path/to/repository \
  -query "reject workspace paths that escape through symlinks" \
  -top-k 5

./bin/deltacode slice \
  -root /path/to/repository \
  -path pkg/workspace/workspace.go \
  -target ResolveFile

./bin/deltacode context \
  -root /path/to/repository \
  -objective "reject workspace paths that escape through symlinks" \
  -top-k 5

Running deltacode

with no arguments starts the stdio MCP server bound to the current directory. Set the root explicitly with deltacode mcp -root /repo

. The server exposes:

discover_symbols

slice_symbol

context_for_task

Example configuration:

{
  "mcpServers": {
    "deltacode": {
      "command": "/absolute/path/to/deltacode",
      "args": ["mcp", "-root", "/absolute/path/to/repository"]
    }
  }
}

Every file request is resolved under the process-configured repository root. Absolute paths, ..

escapes, symlinks, non-regular files, oversized files, and unsupported source types fail closed.

go run ./cmd/deltacode-bench \
  -root /path/to/checked-out-repository \
  -cases /path/to/cases.json \
  -top-k 5 \
  -out result.json

The report binds the case-file hash, source manifest hash, runtime, per-case rankings, and aggregate metrics. Benchmark cases must be frozen before tuning.

The discovery ranker currently indexes Go functions and methods. The slicer supports Go and Python. DeltaCode proposes context; compilers, tests, policy controllers, and human review retain authority over edits and execution.

The earlier Model2Vec/bbolt prototype is preserved on the experimental/vector

branch and is not part of the v0.1 release.

Apache License 2.0.

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