Agent Skills vs Visiby: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Agent Skills and Visiby — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Agent Skills

Addy Osmani

Free

Open-source library of production-grade engineering skills that make AI coding agents follow senior-engineer workflows across the full dev lifecycle.

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.

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.

FNA Technology

Paid

AI visibility platform that tracks how ChatGPT, Perplexity, Claude, Gemini and AI Overviews cite your brand, and ships fixes.

AI Citation Tracking: Continuously samples roughly 50,000 prompts per week across ChatGPT, Claude, Perplexity, Gemini and Google AI Overviews to record where and how a brand is cited.
Per-Engine Visibility Scoring: Reports a composite AI Visibility score plus share of voice and prompts won or lost, broken out engine by engine so declines can be traced to a specific model.
Prompts & Citations Explorer: Lets teams open any tracked prompt and read the actual model answer to see which competitor was named and why.
Brand Entity Analysis: Maps the adjectives each engine associates with your brand versus competitors and suggests reframing plays to change that portrait.
Competitor Intelligence: Tracks rival citation share on comparison and 'alternatives to' prompts, highlighting categories where a competitor dominates.
Prioritized Action Plan: Converts findings into P0/P1 recommendations such as schema additions or comparison pages, each with a time estimate and projected score gain.
Site Audit for AI Parseability: Audits pages for missing entity definitions, structured Q&A data and other signals that prevent models from citing the site correctly.
White-Label Reporting and API: Higher tiers add white-label client reports, SSO/SAML and API access for agencies managing multiple brands.

AI Search Monitoring: Marketing teams track whether ChatGPT and Perplexity recommend their product or a competitor on high-intent category prompts.
Competitive Benchmarking: Brands quantify how much citation share a named rival is capturing on 'alternatives to' and 'best of' queries.
Content Prioritization: Content teams decide which pages to write or refresh based on which prompts are currently missed rather than on keyword volume alone.
Technical AEO Audits: SEO specialists find pages lacking FAQ schema or entity markers that keep answer engines from parsing them.
Agency Client Reporting: Agencies run pooled prompt tracking across multiple client workspaces and deliver white-label AI visibility reports.
Executive Reporting: Operators present a weekly digest showing search clicks alongside AI citation share to explain traffic shifts leadership sees.