Borrowing it
Nothing to install: this file belongs to manthanpatelll/claude-code-starter. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/manthanpatelll/claude-code-starter/main/.claude/skills/e2e/SKILL.mdgit clone --depth 1 https://github.com/manthanpatelll/claude-code-starterWrote 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/manthanpatelll/claude-code-starter/e2e)<a href="https://agentmods.dev/skills/manthanpatelll/claude-code-starter/e2e"><img src="https://agentmods.dev/badge/skills/manthanpatelll/claude-code-starter/e2e/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/manthanpatelll/claude-code-starter/e2e"><img src="https://agentmods.dev/badge/skills/manthanpatelll/claude-code-starter/e2e.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00053 | $0.00221 |
| Opus 5.5 | $0.00021 | $0.00088 |
| Sonnet 5.5 | $0.00011 | $0.00044 |
| Haiku 4.5 | $0.00005 | $0.00022 |
Grade A, and why
e2e 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 1mo 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.
What it actually says
E2E
Runs the test suite, triages failures, and fixes flake without quietly changing product behaviour.
Workflow
- Run the suite (e.g.
npx playwright test). Scope to a flow if one is given. - For each failure, decide the category before touching anything:
- Real bug -> report it, do not "fix" the test to pass.
- Outdated test (spec changed on purpose) -> update the test.
- Flake (timing/race) -> stabilize with proper waits, not sleeps.
- Re-run a fixed test a few times to confirm it is no longer flaky.
Hard rule
Never weaken an assertion just to make CI green. A flaky pass is worse than an honest fail.
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.
- 1mo ago First seen · 24 lines · 53 tokens per session scan A 64b378bb8cee
e2e is a skill published in the GitHub repository manthanpatelll/claude-code-starter (21 stars, last pushed 5mo ago), licensed MIT. It adds 53 tokens to every session and 221 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
Other skills, from other repositories
verify-omnigent
Drive Omnigent the way a user does and prove a behavior with recorded evidence, using an isolated server, runner, and mock model plus a feature map of every user entry point. Load before reproducing a user-facing bug, before claiming a fix works, or when reviewing whether a change covered every surface (session vs.…
test-master
Generates test files, creates mocking strategies, analyzes code coverage, designs test architectures, and produces test plans and defect reports across functional, performance, and security testing disciplines. Use when writing unit tests, integration tests, or E2E tests; creating test strategies or automation…
eval-dataset-design
A guide to creating reliable test sets for AI agents. Each evaluation task includes the request, the simulated user's behaviour, a reset starting state, and a success check that can be independently verified.
dogfood
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.
cua-driver
Use Cua Driver for desktop or browser tasks that are awkward or unavailable through Bash/APIs, or when the user explicitly wants GUI interaction: app testing, visual bug reproduction, form filling, calendar entry, screenshots, and demo recording. Also covers Cua setup; not OpenAI Codex Computer Use or web research.
critique
Adversarial design critique of the current work. Render it, look at it, and argue for rejection. Run after the gates are green, never instead of them.