Hlido

OpenTakeoff

Specialized verticals · tested 2026-08-09 · re-test due 2026-11-09 · by the Hlido desk, not the vendor

In short: Browser-local construction takeoff that records how every measurement was made — by a person, by one click, or by an agent — which is the right provenance model for a document that ends up in a bid.

4 PASS · 3 FAIL of 7 public-surface claims

Visit OpenTakeoff → scorecard.json

Quick answer

OpenTakeoff scores 70/100 (STEADY) on Hlido’s independent, hands-on test (reviewed 2026-08-09). STEADY (70) for solving a real trade problem with a genuine constraint respected (plan sets never leave the browser), Apache-2.0 licensing, and an unusually sound provenance model that records whether each measurement ca Pricing: Open source (free entry point documented).

Hlido Editor · 2026-08-09

OpenTakeoff is an Apache-2.0 quantity-takeoff tool that runs entirely in the browser: drag in a PDF, an image or a whole zip plan set, set or auto-detect the scale, and trace areas, cut-outs and markups against named conditions. Two decisions stand out on the captured surface. First, 'nothing leaves your browser' — for contractors, plan sets are commercially sensitive and often under NDA, so a local-only tool removes a real adoption blocker rather than a theoretical one. Second, and more interesting for an agent register: the app states that every measurement keeps its scale and how it was made — a person, one click, or an agent — over one shared engine. That is provenance at the measurement level, and it is exactly what a takeoff needs, because a quantity that feeds a bid has to be auditable regardless of who or what produced it. Most tools bolting on AI assistance treat human and machine output as interchangeable; recording the difference is the more honest design. The surface is the running application rather than a marketing page, so what Hlido could verify is the UI itself: conditions, waste percentages, fill styles, scale setting, voice command, zone and snap aids, and a sample medical-centre floor-finish plan for first use. What is not visible anywhere is the agent interface it advertises — no MCP endpoint, API documentation or integration guide was reachable — along with no accuracy evidence, no version and no adoption. The agent claim is therefore stated but unverified.

Why STEADY

STEADY (70) for solving a real trade problem with a genuine constraint respected (plan sets never leave the browser), Apache-2.0 licensing, and an unusually sound provenance model that records whether each measurement came from a person, a click or an agent. Held below VITAL because the agent-facing path it advertises is not documented anywhere reachable — 'point an AI agent at the same engine' is a claim with no visible interface behind it — and because there is no accuracy evidence, version or adoption on the surface.

Public-surface checklist

What we saw

1 screenshot captured by the Hlido engine during the reviewed run (run-5ab1555bb2361361-opentakeoff-netlify-app). Our own captures — not vendor marketing material.

OpenTakeoff — run screenshot 1 (home.png)
home.png

What it does well

What it fails at

Red flags

Best for

  • Estimators and small contractors who need takeoff without sending client plan sets to a vendor
  • Anyone wanting an open-source alternative to per-seat commercial takeoff software
  • Teams that need to know whether a quantity was measured by a person or produced automatically

Not recommended for

  • Agent-driven workflows today — the integration path is advertised but not documented
  • Multi-user collaboration or centralised project storage
  • Work requiring validated measurement accuracy or a vendor support commitment

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 2026-08-09.

Related agents

Agent relevance

No programmatic surfaces

Agentic-Commerce Readiness 32/100 · SURFACE-ONLY

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

The application advertises that an AI agent can be pointed at the same measurement engine as a human, and it records agent-produced measurements distinctly — but no MCP endpoint, API reference or integration guide is reachable from the public surface, so the path cannot be confirmed or used today.

Agent-friendly score: 3/10

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-2+editorial-narrative-v2 · Methodology version 2026.05 · Next review due 2026-11-09

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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Hlido trust score

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