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/sei-newbear/xp-harness/e2enpx skills add sei-newbear/xp-harness --skill e2egit clone --depth 1 https://github.com/sei-newbear/xp-harnessWrote 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/sei-newbear/xp-harness/e2e)<a href="https://agentmods.dev/skills/sei-newbear/xp-harness/e2e"><img src="https://agentmods.dev/badge/skills/sei-newbear/xp-harness/e2e.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 | $0.00149 | $0.00584 |
| Opus 5 | $0.00075 | $0.00292 |
| Sonnet 5 | $0.00030 | $0.00117 |
| Haiku 4.5 | $0.00015 | $0.00058 |
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 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.
What it actually says
E2E テストの流儀
プロジェクトの E2E の流儀 (spec の書き方・構造・命名) を spec 作業に効かせるためのスキル。流儀そのものはプロジェクト側にあり、このスキルはそれを探して効かせる入口。E2E を動かす手順 (環境・コマンド・CI) は e2e-execution skill の責務。
関連する E2E の流儀を探して従う
このスキルが呼ばれるたびに、以下を行う（1 つの作業の中で触る範囲が別の領域に移ったら、その都度やり直す）:
- 触る範囲を特定する: いま読み書きしようとしているファイルのディレクトリ / 領域を特定する（例: front 配下と api 配下で流儀が分かれている場合、どちらの領域の作業かを特定する）
- 範囲に対応する E2E の流儀を探す:
- セッションに登録されているスキル（このスキル自身を除く）にその範囲の E2E の流儀を扱うものがあれば、（参照して読むのではなく）スキルとして呼ぶ
- スキルでない規約ファイル（その領域のディレクトリ配下の CLAUDE.md / AGENTS.md 等のドキュメント）があれば、読む
- 見つけた流儀に従って作業する
- 見つからなければ、流儀をでっち上げない: 一般に良いとされる判断で進める
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 · 20 lines · 149 tokens per session scan A eb8c2b80e74d
e2e is a skill published in the GitHub repository sei-newbear/xp-harness (9 stars, last pushed 27d ago), licensed MIT. It adds 149 tokens to every session and 584 once invoked, about $0.0007 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.
Other skills, from other repositories
use-agent-browser-for-airi
Test AIRI display-model imports with agent-browser across stage-tamagotchi Electron, stage-web, and stage-pocket mobile web layouts. Use when uploading and verifying contributor-supplied Live2D ZIP, VRM, or MMD ZIP/PMX/PMD files through AIRI's model selector, including onboarding bypass, format-specific import…
verify
Exercise the real app/API/CLI and collect observable evidence; tests alone do not count as end-to-end verification.
solopi-ai
通过 SoloPi 的机器可读 CLI 编译和执行 AI 验证计划，管理签名端侧 ExecuTorch 决策模型、持久设备池、无人值守任务、安卓设备、应用、动作、配置、用例步骤与交互录制、回放及性能历史、动态 Agent、批量与重复执行、性能监控、压力测试和证据。适用于需求/AC 到 Result Judge 三态结论、cloud/on-device 决策切换、模型发布门禁，以及 generation 租约的多设备 CI 执行。.
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.
local-frontend-check
Smoke-test or verify UI behaviour on the local Jarvis Registry frontend running at http://localhost/gateway. Use for manual regression checks, bug-fix verification, and end-to-end confirmation of specific flows without running the automated test suite.
pr-integration-test
Design, implement, and validate Intelligent Terminal integration tests for a target pull request or regression. Use when asked to add PR integration tests, convert a bug fix into E2E coverage, prove existing behavior still works, map tests to the release checklist, or verify E2E reports mark checklist cases complete.