gi-dellav/zerostack

Coding · tested 2026-07-21 · re-test due 2026-10-19 · by the Hlido desk, not the vendor

In short: A lean Rust coding agent built for low memory and speed, with a genuinely clever parallel-worktree design — promising and fast, but earlier-stage than the incumbents.

2 PASS · 3 FAIL of 5 public-surface claims

Quick answer

gi-dellav/zerostack scores 70/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-07-21). STEADY (70) because the design choices are genuinely strong — Rust for footprint, ACP support, and the parallel-worktree concurrency model are real engineering, and permissioned file access is a good safety default. Pricing: Open source (free entry point documented).

Zerostack is a coding agent written in Rust with an explicit optimisation target most tools ignore: memory footprint and performance. It wraps OpenRouter (default), OpenAI, Anthropic, Gemini and Ollama, streams tokens, and reads/writes/edits/searches your codebase with user-controlled permissions on what it may touch. Two features stand out as more than table stakes: it ships an ACP server so editors like Zed can connect to it as an agent, and it can run multiple zerostack agents on the same repository simultaneously — each in a temporary git worktree, with changes merged when the agent exits, no manual worktree juggling. It also does multimodal input (images, audio, PDF) and has an 'Advisors' feature where cheaper models escalate hard tasks to expert LLMs. The built-in slash commands (frontend-design, review-security, simplify, autoconfig) show a thoughtful product mind. The honest framing: this is GPL-3.0 (copyleft — matters for how you can reuse it), the community is smaller than the established CLI agents, and as a younger project the durability and real-world reliability track record simply isn't there yet. It's a credible, well-designed entrant rather than a proven default.

Why STEADY

STEADY (70) because the design choices are genuinely strong — Rust for footprint, ACP support, and the parallel-worktree concurrency model are real engineering, and permissioned file access is a good safety default. Not higher because it's earlier-stage than the incumbents: smaller community, GPL-3.0 copyleft to weigh, and limited independent evidence of reliability over time. A tool to watch and try, not yet a safe default.

Public-surface checklist

What we saw

1 screenshot captured by the Hlido engine during the reviewed run (run-d1ad26ffd410e600-gi-dellav-github-io). Our own captures — not vendor marketing material.

gi-dellav/zerostack — run screenshot 1 (home.png)
home.png

What it does well

What it fails at

Best for

  • Developers who want a fast, low-footprint coding agent they can run many of at once
  • Zed / ACP users wanting a native agent connection
  • Users who value explicit permission control over file access
  • Rust-friendly teams comfortable adopting a younger, well-designed tool

Not recommended for

  • Teams that need GPL-3.0-incompatible licensing
  • Buyers wanting a mature, widely-battle-tested default agent
  • Non-technical users needing a polished GUI and vendor support

Pricing & access

Derived from Hlido-held evidence only (engine checklist + editorial text); quotes are verbatim from the scorecard; not vendor-supplied; re-derived daily. Verify current prices on the vendor's pricing page. Last verified 2026-07-18.

Compared to

Agent relevance

CLI Behavioral-testable

Agentic-Commerce Readiness 44/100 · SURFACE-ONLY

Independent readiness for agent delegation & transaction. How it’s scored · check live

Good. Ships an ACP server so editors/other tools can drive it as an agent, and its parallel-worktree model makes it suitable for orchestrating multiple concurrent coding agents. CLI-first; no REST API or MCP surface documented yet.

Agent-friendly score: 6/10

Evidence

scorecard.json · transparency passport · registry · methodology

More: compare agents · best of · developer tools · incident registry

Verdict by Hlido Editor, our automated editorial system · Method: public-surface-tier-1+editorial-narrative-v2 · Methodology version 2026.07 · Next review due 2026-10-19

How this page was produced. The scores, claim verdicts and evidence come from automated hands-on testing of the product’s public surface. The written analysis is drafted by an AI system, and pages publish without a person reviewing each one. Hlido publishes this record and answers for it — tell us if anything here is wrong and we will correct it.

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