Autonomous QA for iOS + web β agents get a deterministic ship/no-ship verdict, no test code
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent β or use 1-click editor setup below.
π‘ Paste into ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows)
Tapp is the release-contract and evidence layer for teams shipping agent-authored applications. It turns a repository and real product into an observed UI Map, a compact reviewed deterministic suite, and an inspectable merge decision.
Coding agents can write the code, and (with Playwright & friends) they can even drive the app.
What nobody gives them is judgment: did it actually work? tapp explores your app like a user β
no test code, no app changes β detects what's broken, and commits to a verdict your merge queue
can trust: ready, caution, or blocked, with evidence.
Three platforms, one judgment layer:
href="#" links, error pages), and the same verdict.Requirements: Node β₯ 18. iOS needs macOS + Xcode; Android needs adb plus a connected
emulator/device; web needs Playwright + Chromium.
From the app repository, let the agent see the current screen and then ask for a release verdict:
Claude Code can read the saved image with its file-reading tool; Codex can open it with
view_image. The agent should report what the screenshot proves, preserve Tapp's exact
ready/caution/blocked verdict, and link the HTML evidence report. No server, account, config
file, test code, API key, or bundle id is required for this loop.
The product, executable, and package leaf are all Tapp: npm distributes it as
@aarwitz/tapp, while the installed command remains tapp.
To bootstrap maintained release infrastructure, preview the repository model and grounded plan before Tapp writes anything:
The baseline command writes only after autonomous QA and every selected deterministic suite pass
conclusively. It stores .tapp/baselines/<platform>/<target-id>.json; the generated workflow
uses that exact target identity so two apps on the same platform never share a baseline. ci install writes .github/workflows/tapp.yml plus .tapp/ci.json, refuses unresolved build
configuration and existing-file collisions, and never commits, pushes, enables branch protection,
or creates GitHub resources. Review and pin the generated Tapp release reference to its immutable
commit SHA before production.
Every verb takes whatever you have: nothing (auto-detects the repo you're in, or the app
already on the simulator), a repo directory, a path/to/App.app, or a bundle id:
Web (beta): npx -y @aarwitz/tapp qa http://localhost:3000 (one-time setup:
npm i -g playwright && npx playwright install chromium)
Focused web inspection waits briefly for loading states to settle. If a consent or location modal blocks the screen, dismiss it and wait for the content you care about in the same package-only call:
Android:
Optional but recommended (prebuilds the test harness so the first run is fast):
npx -y @aarwitz/tapp app . opens a local Release Studio for people who want visual repository
onboarding, release-plan review, and CI preparation. It is not required for the coding-agent
open/qa workflow.
The MCP server adds the two things a CLI can't do: screenshots inline in your agent's context (the model literally sees the screen) and the interactive session loop (tap β read tree β type, with the app staying open between actions).
Claude Code:
Cursor / VS Code (Copilot) β add to ~/.cursor/mcp.json (Cursor) or .vscode/mcp.json (VS Code):
Codex CLI β add to ~/.codex/config.toml:
Any other MCP client: stdio command npx -y @aarwitz/tapp mcp.
Then ask your agent:
"Run tapp qa on my app β is it ship-ready?" "Open com.mycompany.app on the simulator and screenshot the home screen." "Log in with test@example.com, drive to checkout, and record it as a replayable test."
| Tool | What it does | |
|---|---|---|
| π | tapp_open_app | See a screen β launch the app, return screenshot + accessibility tree. Seconds. |
| πΈ | tapp_screenshot | Whatever's on the sim right now, as an inline image. |
| π³ | tapp_ui_tree | The accessibility tree of the current screen (ids, labels, hittability). |
| πΉ | tapp_session_start/act/end | Interactive driving β the Playwright loop. App launches once; each act (tap/type/swipe/back/wait) returns the fresh tree. |
| π§ͺ | tapp_run_qa | Autonomous QA β explores with no authored test, returns {verdict, releaseScore, findings[]} (releaseScore is null for exploratory web). Takes appBundleId (iOS), androidAppId (Android), or url (web). |
| π§ | tapp_init | Repository import β detect targets; optionally explore a real surface; persist the shared UI Map; construct the evidence-classified model and grounded release plan. |
| π€ | tapp_actor_config | Actor/session setup β store roles, isolation/provisioning, and environment-variable names without accepting or persisting credential values. |
| β | tapp_release_plan | Release-plan lifecycle β inspect, approve/reject/defer, generate, real-target validate, and explicitly promote proposed guarantees without silent test edits. |
| π¦ | tapp_ci_setup | Baseline and CI setup β import a conclusive target baseline or render/install the same reviewable target-aware workflow as the CLI. |
| πΊοΈ | tapp_ui_map | Persistent UI Map β build, inspect, merge, and diff observed states, controls, transitions, provenance, and coverage. |
| π§© | tapp_task | Reusable deterministic Tasks β validate and compile shared actions such as signIn against the UI Map; replay stays keyless. |
| π | tapp_release_contract | Business-level release contracts β validate, compile, or run typed guarantees composed from Tasks and named actors. |
| π | tapp_pr_plan | PR-aware evolution β select reviewed contracts, schedule bounded changed-surface exploration, and explicitly adopt observed coverage proposals without silent rewrites. |
| π | tapp_flow_run / flow_save / flow_generate | Deterministic E2E execution (Flows) β raw steps or reusable Task calls replay with exact assertions. |
| π₯ | tapp_scenario_run | Multi-actor system tests β isolated named browser sessions verify cross-account state with deterministic assertions. No AI at replay time. |
| π± | tapp_list_simulators / boot_simulator / install_app | Simulator + app management. |
| π©Ί | tapp_health, tapp_capture*, tapp_parse_markers | Diagnostics and capture history. |
Full agent playbook: AGENTS.md β ships inside the package so agents can read it too.
Application-model and import contract: docs/application-model.md.
The desktop Coverage view reads the same .tapp/application-model.json,
.tapp/release-plan.json, and .tapp/ui-map.json, including explicit proposal review; it
does not maintain a separate product model. Map nodes identify both the real launch entry and the
deterministic per-platform navigation root used for bounded changed-surface replay.
Adaptive exploration, deterministic judgment. Exploration is adaptive β two runs may traverse different paths through your app. Judgment is deterministic: the same evidence trace always produces the same findings and verdict β no LLM variability in the decision loop. PR gating keys on the regression diff (stable finding signatures vs. a baseline), so it reacts to what changed, not to run-to-run path variance. For critical user journeys, committed Tasks and Flows provide the stable CI suite: reusable semantic actions, exact assertions, condition-based waits, fresh launch state, bounded timeouts, and evidence on failure. We call this flake-resistant, not magically flake-freeβbackend outages, unstable test data, and poorly identified controls can still make any E2E test fail.
Native has a heuristic release score; exploratory web does not. The native 0β100 number comes from fixed deductions and is not calibrated probability. Web reports deterministic findings, advisory budget-capped control probes, and concrete coverage instead of compressing those unlike signals into a scalar. Committed Flows, Tasks, contracts, and baseline regressions provide the web merge decision.
tapp_run_qa explores like a user β accessibility surfaces on iOS/Android and a real browser on web β
and detects crashes, failed sign-ins, dead buttons, stuck loading screens, error surfaces,
navigation loops, and dead ends (plus, on web: uncaught JS exceptions, failed/5xx requests,
broken links and assets, and visible placeholder links with no destination). The verdict is
deterministic (no LLM in the run loop) and honest:
blocked β a release-blocking issue was found.caution β issues to review, or the run couldn't see enough.ready β genuinely explored with no detected blockers in the checks that ran. A shallow run
is never ready β if the
app crashed on launch or a login wall blocked exploration, you get inconclusive: true,
not a false pass. Absence of findings is not a pass.Web beta presents a ready result as AUTOMATED CHECKS COMPLETE, not βship-ready,β and displays
no scalar score. Exhaustive checks on each exercised page drive the verdict; sampled control probes
remain visible findings but are advisory. The report
explicitly excludes content/claim accuracy, privacy and API data minimization, brand/SEO
consistency, and subjective visual credibility. Those require reviewed contracts, privacy review,
or human/vision judgment; an exploratory crawl must not imply they were validated.
For a business guarantee such as βevery coach is insured,β use a deterministic app-owned verifier endpoint that returns success only when the invariant holds, then require that status and the customer-visible claim in a release contract. The current DSL does not yet read arbitrary JSON response bodies or compare a cross-origin API payload directly with page copy; use a verifier or an explicit CI preflight rather than assuming autonomous QA inferred the guarantee.
Apps behind a login? Pass testEmail/testPassword (typed into the login form automatically),
appLaunchArgs (e.g. ["--uitesting"] if your app supports a bypass), or explicit loginSteps
for custom login UIs.
The same engine runs as a merge gate β explore on every PR, replay committed release contracts, Flows, and multi-actor Scenarios, diff findings against the last conclusive default-branch run, fail on regressions, post a sticky PR comment, and upload screenshots, the recording, and machine-readable JSON:
On pull requests, the Action automatically reads the complete changed-file set from GitHub,
retaining old and new paths for renames. It always runs critical/policy.always contracts, adds
contracts related through reviewed source ownership, the UI Map, and transitive Task composition,
and records skipped contracts and coverage gaps in tapp-pr-plan.json. A selected contract that
does not execute blocks the merge. Set pr-selection: "false" only when intentionally running the
full contract set.
Changed weakly covered surfaces are not limited to direct web URLs. Reviewed Task source ownership can compile one bounded native target (or up to five web targets) through observed UI Map edges, with condition waits and stable target evidence. Missing or failed targets make the run inconclusive; Tapp does not guess a path from a screen name.
The first successful, conclusive run on main seeds a repository-scoped Actions cache and a
90-day baseline artifact. Both are keyed by platform and stable application-model target id. Pull requests automatically restore it and fail only on new
high/critical findings or broken Flowsβnot pre-existing debt. No baseline commit or PAT is required.
If you prefer a reviewed, durable baseline, run tapp baseline create and commit the generated
.tapp/baselines/<platform>/<target-id>.json; tapp ci install wires its explicit path into the
corresponding job. The legacy .tapp/baseline.json is still recognized. Automatic baseline restore and the PR comment need actions: read and
pull-requests: write as shown above. Secrets are unavailable to workflows from forks, so
auth-gated apps should either use a non-secret UI-testing launch argument or skip the gate for
untrusted forks.
Already build the simulator app in another job, or use another CI provider? The portable command
accepts that .app, detects its bundle id, writes report artifacts, and exits non-zero when the
gate fails:
See the self-test at .github/workflows/tapp-gate-example.yml for Flows, auth inputs, and other controls. GitHub-hosted iOS runs require a macOS runner; the first run also builds the XCUITest harness, so budget roughly 5β10 minutes depending on app size.
Android CI runs on Linux with an emulator/device already connected. The Action can build the APK or accept a prebuilt one:
For web, pass platform: web plus web-target: and Tapp uses the application model to run its
lockfile-backed install/build, start a detected package script or read-only static server, wait for
readiness, gate it, and stop it even on failure. Pass url: instead for an already-running owned
environment. Add
scenarios: .tapp/scenarios/*.yml to gate isolated cross-account journeys; see
docs/scenarios.md. Automatic
baselines are isolated by platform and target, so two same-platform apps are never compared.
The hosted service is under development and is not currently offered for customer repositories. Do not upload private code or credentials to an old preview. The retained cloud prototype is not the production SaaS boundary. Use the local Release Studio and the portable GitHub Action in infrastructure you control until the new account, tenant authorization, private evidence, and isolated-worker boundary passes security review.
Drop this into your repo's AGENTS.md (read by Codex, Cursor, Copilot, Devin, Zed, β¦) so
your agent proves its UI work instead of claiming it:
Every driver speaks one protocol: structured OCQA_* markers (state, actions, issues,
transitions) that the judgment layer parses into trees, screenshots, findings, and the verdict.
On iOS, a generic XCUITest harness attaches to any app by bundle id β no SDK or app code
changes β and acts through the accessibility tree. On Android, ADB + UIAutomator provide the
same black-box driver contract. On web (beta), a deterministic Playwright crawler does the
same in a real browser. Same detectors' spirit,
same dedup, same regression gate, same honest verdict. Core exploration, evidence collection, and
verdict calculation run entirely locally β no telemetry, nothing phones home. Optional AI
features are explicit: finding enrichment requires TAPP_ENABLE_REMOTE_AI=1 (an ambient
API key alone never changes data handling), and AI flow generation / assert_ai only run
when you invoke them; these send selected metadata (screen names, finding titles) to your
configured model provider. Runtime configuration uses TAPP_* environment variables. Repository
artifacts live under .tapp/, and desktop run configuration uses .tapp.yml. Existing
.autotap/, .autotap.yml, and AUTOTAP_* inputs remain readable as migration fallbacks; when
both names exist, Tapp uses the canonical one. Rename the old directory/config in your next
reviewed repository changeβno secrets or evidence formats need to be rewritten.
Committed Flow replay, recording a driven session, autonomous exploration, exact assertions,
regression comparison, and CI gating require no API key and no coding agent at runtime. AI is
only an optional authoring/enrichment layer (tapp_flow_generate, assert_ai, finding enrichment).
The first tool call builds the harness once (~2 min, cached in ~/.tapp; rebuilt automatically
if you switch simulators). All captures land in ~/.tapp/captures/.
The macOS cockpit is frozen as a supported native interface and parity floor; it still reads the canonical Application Model, release plan, and UI Map in Coverage. Its older import/build path is not yet a thin client of the shared product-operation layer, so new product work is converging in the browser without deleting or reducing the desktop experience.
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