Agent Skills vs sizeless: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of Agent Skills and sizeless — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
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Agent Skills
Addy Osmani
Open-source library of production-grade engineering skills that make AI coding agents follow senior-engineer workflows across the full dev lifecycle.
Key features
- Lifecycle Slash Commands: Seven commands (/spec, /plan, /build, /test, /review, /code-simplify, /ship) that map to each phase of development.
- Auto Build Mode: /build auto generates a plan and implements every task autonomously after a single approval.
- Test-Driven Execution: Each task is test-driven and committed individually, pausing on failures or risky steps.
- Automatic Skill Activation: Skills activate based on what the developer is currently doing, without manual selection.
- Quality Gates: Encodes review and QA gates so agents enforce code-health standards before shipping.
- Spec-First Workflow: Enforces writing a spec and plan before code to keep agent output structured.
Best for
- Structured Agent Coding: Guide an AI coding agent through spec, plan, build, test, and ship in a disciplined flow.
- Autonomous Feature Builds: Approve a plan once and let the agent implement all tasks with per-task tests.
- Code Review Automation: Apply consistent review and simplification gates before merging.
- Onboarding Best Practices: Encode senior-engineer workflows so every project follows the same quality standards.
- Reducing Manual Steps: Cut the human hand-offs between tasks while preserving verification.
sizeless
sizeless
Turns a smartphone video of an open trench into a centimetre-accurate 3D point cloud, CAD as-built plan and GIS-ready digital twin of buried utilities.
Key features
- Smartphone capture: Field crews record an open trench with a standard iPhone Pro — no specialist scanning hardware and no separate surveying appointment
- Centimetre-accurate point clouds: Reconstruction algorithms developed at ETH Zurich build a high-resolution 3D point cloud of the excavation from the video alone
- Standards-compliant CAD output: Generates as-built plans in DWG and DXF, with couplings and pipe runs identified and measurements simplified
- 3D digital twin and GIS export: Produces a model of the pipe route including building entries that drops into existing GIS systems
- Works without GPS: Captures basement sections and building entry points where GNSS-based surveying fails
- Immediate backfilling: Because capture takes minutes, trenches close right after filming instead of waiting on a survey crew
- Documentation in about 72 hours: Complete records arrive weeks earlier than conventional surveying, enabling prompt connection billing
- Third-party utility capture: Records crossing utilities and as-laid geometry as unbroken 3D evidence, replacing hand sketches
Best for
- A utility network operator documenting residential service connections without booking a surveyor for every site
- A contractor closing a trench the same day instead of leaving it open pending a survey appointment
- Capturing a building entry point in a basement where GPS-based surveying cannot get a fix
- A district heating project producing as-built DWG plans for regulatory sign-off
- Spotting a laying error in the 3D point cloud before backfilling, while the fix is still cheap
- Feeding as-built pipe geometry into a GIS system for long-term network maintenance planning