Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/schalkneethling/webdev-agent-skills/frontend-testingnpx skills add schalkneethling/webdev-agent-skills --skill frontend-testinggit clone --depth 1 https://github.com/schalkneethling/webdev-agent-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/schalkneethling/webdev-agent-skills/frontend-testing)<a href="https://agentmods.dev/skills/schalkneethling/webdev-agent-skills/frontend-testing"><img src="https://agentmods.dev/badge/skills/schalkneethling/webdev-agent-skills/frontend-testing.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00066 | $0.02742 |
| Opus 5 | $0.00033 | $0.01371 |
| Sonnet 5 | $0.00013 | $0.00548 |
| Haiku 4.5 | $0.00007 | $0.00274 |
Grade A, and why
frontend-testing scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 356 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Frontend Testing
Start by writing tests that validate acceptance criteria. Then add implementation tests where they provide value.
Core Principle
"The more your tests resemble the way your software is used, the more confidence they can give you." — Kent C. Dodds
This principle guides testing decisions, but isn't the whole picture:
- Acceptance criteria tests verify the system does what users/stakeholders need. These should be stable across refactors.
- Implementation tests verify the pieces are robust — edge cases, error handling, complex logic. These may change when you refactor.
Both have value. The anti-pattern to avoid is tests that only mirror implementation without validating meaningful behavior.
When to Load References
Load reference files based on test type:
- Unit tests with DOM:
references/locator-strategies.md - E2E tests:
references/locator-strategies.md,references/aria-snapshots.md - Visual regression tests:
references/visual-regression.md - Accessibility audits:
references/accessibility-testing.md - Structure validation:
references/aria-snapshots.md— consolidate multiple assertions into one - All tests: Start with this file for core workflow
Workflow
Step 1: Start with Acceptance Criteria
Before writing any test, identify what the code should do from the user's perspective.
Ask for or extract criteria from:
- Ticket description or user story
- Figma annotations
- Functional requirements
- Product owner clarification
Document criteria as a checklist. These become your first tests.
Write acceptance tests before reading implementation. This prevents circular validation where tests just confirm "code does what code does."
Step 2: Map Criteria to Test Cases
For each criterion, identify:
- Happy path: Normal expected behavior
- Edge cases: Boundary conditions
- Error cases: Invalid inputs, failures
Example mapping:
Criterion: "User can filter products by category"
├─ Happy path: Select category, products filter correctly
├─ Edge case: No products match filter, show empty state
├─ Edge case: Clear filter, all products show again
├─ Error case: Filter API fails, show error message
└─ Accessibility: Filter controls are keyboard accessible
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 4d ago First seen · 356 lines · 66 tokens per session scan A 39e58d18151d
frontend-testing is a skill published in the GitHub repository schalkneethling/webdev-agent-skills (7 stars, last pushed 4mo ago), licensed MIT. It adds 66 tokens to every session and 2,742 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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