Agent-QA vs Guildly

Agent-QA and Guildly are both coding assistants tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Agent-QA

The tool lets you write test steps in plain language — 'Click on the Create issue icon', 'Verify that the created issue is shown' — and an agent translates those into browser actions at runtime, reading visible labels and screen state instead of fragile CSS selectors. After each run, it builds execution memory: observations about navigation contracts, UI quirks, and previously healed steps, which get injected into future runs so the agent stops rediscovering the same UI patterns. Self-healing means that when a component shifts, the agent iterates through recovery attempts rather than failing immediately. The ceiling appears when test logic branches on conditional application state — the YAML authoring model is built for linear flows, and complex branching sends teams back to scripting.

Guildly

Each agent has a fixed role: PM writes PRDs, Manager routes tickets, SDEs work in isolated git worktrees, Reviewer signs off before anything merges. Every action traces back through a chain — line of code to ticket, ticket to PRD, PRD to the #general message that started it. The audit trail isn't a report you run after the fact; it's the structure the system runs on. That structure is also the ceiling: teams needing agents to adapt their process mid-sprint, or handle workflows that don't fit the six-role model, will hit the playbook's edges before long. The tool is in beta, with no API and no self-hosted option, so the surface you can extend is narrow.

Attribute	Agent-QA	Guildly
Pricing	Paid	Free
Free trial	No	No
Open source	Yes	No
Has API	Yes	No
Self-hosted option	Yes	No
Platforms	Web and mobile (Chromium, mobile drivers)	macOS
Pros	Natural language test authoring against visible UI labels rather than DOM selectors, so a component rename or layout shift does not immediately break the test suite the way a hard-coded selector would. Execution memory that accumulates across runs with trust scores and confirmation counts, which means the agent stops wasting run time rediscovering navigation patterns it has already mapped — later assertions stay focused on actual page behavior. Self-healing iteration within a single run — when an action fails, the agent retries with updated screen state observation rather than failing the step immediately, so transient UI delays cause fewer false negatives. Support for custom and open-source LLM models at the infrastructure level, so teams with data-residency requirements or API cost constraints can run inference locally without forking the tool. Open-source codebase with self-hosted deployment option, which means teams are not locked into a vendor's uptime or data pipeline when running tests against internal staging environments.	Deterministic six-role workflow (PM → Manager → SDE → Reviewer) means agents don't improvise or skip steps, so you're not debugging a PR that nobody remembers creating. Full audit chain from code line to PRD to originating conversation, which means tracing a regression takes seconds instead of a git-blame session that still doesn't explain the why. Git worktree isolation per SDE ticket, so parallel agents working the same repo don't stomp each other's files mid-sprint. Model-agnostic agent identity — swapping the underlying LLM doesn't wipe team history or personality, so a model deprecation doesn't mean starting over. Per-agent token dashboard with cost limits on autopilot, so you can walk away without discovering in the morning that the overnight run cost more than you planned.
Cons	The YAML step format is built for linear flows — action, verify, action, verify. Test scenarios that branch based on runtime application state (for example, different assertion paths depending on what a previous step returned from the server) have no native expression in the authoring model. Teams with conditional logic either maintain a parallel scripting layer or restructure tests into multiple flat suites, which defeats the maintenance advantage. Execution memory is only as reliable as the trust scores the agent has accumulated. On a new application or after a major redesign, early runs produce low-confidence observations and the agent behaves closer to a first-run tool — the adaptive advantage appears after repeated runs against a stable-ish UI, not on day one. Teams whose test requirements outgrow linear natural-language flows — particularly those already running Playwright or Cypress suites with custom fixtures, parameterized data, and programmatic assertions — will find agent-qa's authoring model too constrained and switch back to code-first frameworks where branching logic is a function call, not a workaround.	The six-role org chart is fixed — if your project needs a different shape (a dedicated QA agent, a data engineer, a second PM), the structure doesn't bend. Teams with non-standard workflows end up either forcing their process into the existing roles or looking at tools that let them define their own agent topology. No API means you cannot plug Guildly into an existing CI/CD pipeline, a Jira board, or a monitoring stack. Teams that need agents embedded in broader toolchains hit a dead end and move to a framework they can integrate themselves. Beta-only availability with no self-hosted option means you cannot deploy Guildly in an air-gapped or regulated environment. Any team with data residency requirements is blocked entirely.

Bottom line

Agent-QA is paid while Guildly is free; Agent-QA is open source; only Agent-QA exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Agent-QA and Guildly?

Agent-QA is Paid and open source, while Guildly is Free. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Agent-QA better than Guildly?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.