Test Flows
SkillAI & modelsExercises a small or branch-local software change through representative public user or client flows and reports concise observed evidence, defects, ambiguities, and limitations without fixing code, running automated suites, requiring a PR, or preparing formal acceptance; use for lightweight manual-style testing, smoke testing a completed change, or targeted verification after a small fix.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Test Flows skill
What this skill tells your AI
The instructions your AI receives, as published by codagent-ai/agent-skills in skills/test-flows/SKILL.md and read by ahel’s review.
Exercise the checked-out product as a user or real client would. This is a lightweight flow check, not automated validation or formal acceptance preparation.
Inputs
Read the caller-supplied:
- approved behavior or planning artifacts;
- concise implementation summary;
- verification scope: representative full pass or named targeted flows;
- evidence directory when the selected scope includes UI flows or durable evidence is requested.
If expected behavior is unavailable, report what is missing instead of inferring the contract from implementation alone. If a selected UI flow has no evidence directory, report the missing input instead of testing that flow without its required screenshot.
Select flows
For a representative full pass, identify the meaningful changed journeys and public surfaces that
collectively demonstrate the delivered behavior. When an approved test plan exists, exercise its
required and activated conditional AT-* flows. Otherwise keep the inventory proportional to the
small change rather than replaying every requirement scenario or input variation.
For targeted verification, exercise the named affected flows and obvious direct dependencies. Verify the prior finding first. Do not start a new broad review or search unrelated surfaces for additional issues.
Use typical data, configuration, and roles. Do not fuzz, try bizarre inputs, or build an exhaustive edge-case matrix. Test an error or boundary state only when it belongs to a normal selected flow.
Exercise the public surface
Use the project's normal setup, build, install, seed, and start commands needed to expose the current worktree. Do not run automated unit, integration, or end-to-end suites, linters, Validator, or CI.
- Operate web, mobile, desktop, and terminal UIs through their real interface.
- Call APIs through their documented HTTP, SDK, or CLI surface as a client would.
- Invoke CLIs and libraries through their public commands or APIs.
- Trigger background behavior through its normal entry point and inspect the observable result.
For each selected flow, verify resulting state rather than trusting an agent assertion or successful command exit. Continue through independently testable flows after finding a defect; stop only when the problem makes remaining flows unreachable, unsafe, or untrustworthy.
For any tested UI flow, capture a meaningful stable screenshot under the caller's evidence directory. Capture more than one only when multiple states are necessary to understand the flow. Record what the reviewer should notice and a concise text equivalent. For non-visual surfaces, retain a sanitized request/output excerpt or comparable client-visible evidence.
Report
Return a concise report containing:
- checked-out
HEADas context; - each selected flow, action, expected result, observed result, and evidence;
- clear defects with reproduction steps and affected flows;
- product, scope, or design ambiguity separated from defects;
- untested or blocked flows and practical limitations.
Write the same report to a caller-specified path when requested. Do not create status markers or machine-control files.
Do not fix defects, modify approved artifacts, commit, push, wait for CI, inspect PR state, or claim human acceptance. The caller decides how findings are handled and whether targeted verification is needed after a fix.
Signals
- GitHub stars
- 30
- Forks
- 1
- Last commit
- Sep 2026
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test-flows- Source
- github.com/codagent-ai/agent-skills