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/n9e/fe/n9e-config-driven-e2enpx skills add n9e/fe --skill n9e-config-driven-e2egit clone --depth 1 https://github.com/n9e/feWrote 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/n9e/fe/n9e-config-driven-e2e)<a href="https://agentmods.dev/skills/n9e/fe/n9e-config-driven-e2e"><img src="https://agentmods.dev/badge/skills/n9e/fe/n9e-config-driven-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 | $0.00043 | $0.02399 |
| Opus 5 | $0.00022 | $0.01200 |
| Sonnet 5 | $0.00009 | $0.00480 |
| Haiku 4.5 | $0.00004 | $0.00240 |
Grade A, and why
n9e-config-driven-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 2d 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 — 190 lines — stays where its author put it; the contents beside it link to each section on GitHub.
n9e Config-Driven E2E
Use this skill when working on Nightingale config-driven E2E flows. This includes alert-rule creation under e2e/add-alert-rule, and should also guide future flows that start from structured JSON config data. The general pattern is:
JSON 配置数据 -> normalizer 转换为 UI 可读/可操作值 -> Playwright + Midscene 执行页面操作 -> API 回查验证保存结果
This skill is no longer only about adding one alert-rule JSON file. Treat it as the standard way to build E2E coverage for product forms whose source of truth is an exported/API JSON config.
Architecture
- Config files live under a feature-specific
configs/directory, currentlye2e/add-alert-rule/configs/*.json. config-loader.tsdiscovers config files and supportsE2E_CONFIGS=<stem>filtering.reference-data.tsresolves ID-backed fields into visible UI labels.normalizer.tsconverts API/export JSON into a UI-readable normalized model and builds the expected persisted payload.- Step files under
steps/fill page cards or sections from the normalized model. - Datasource-specific query/condition behavior lives under
queries/. - The main test file orchestrates: load config, fetch references, normalize, fill steps, save, API回查, subset assert, cleanup.
Core Principle
Never silently skip a non-default config field.
If JSON contains a meaningful field, do one of these:
- Fill it into the UI through the correct step handler.
- Normalize it into the exact visible UI value first, then fill it.
- Document a real FormNG/API transformation in
buildExpectedAlertRule(). - Fail with a precise TODO only when no UI path exists yet.
Do not delete expected fields merely to make assertions pass.
Source-Code First
Before changing E2E logic, inspect the product code that owns the form:
- Start with
src/pages/alertRules/FormNG/index.tsx. - For API/export config shape vs page form shape, inspect
src/pages/alertRules/Form/utils.ts.processInitialValues()shows how API/export data becomes FormNG form values.processFormValues()shows how FormNG values become save payload.
- For step-card UI:
- Basic/datasource/rule:
FormNG/index.tsx,FormNG/Rule/**, datasource plugins. - Query/trigger:
FormNG/Rule/**,FormNG/components/Triggers/**. - Event handling:
FormNG/PipelineConfigsNG/**. - Effective config:
FormNG/Effective/index.tsx. - Notify config:
FormNG/Notify/**.
- Basic/datasource/rule:
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.
- 2d ago First seen · 190 lines · 43 tokens per session scan A e27c3ff7ead0
n9e-config-driven-e2e is a skill published in the GitHub repository n9e/fe (302 stars, last pushed 2d ago), licensed Apache-2.0. It adds 43 tokens to every session and 2,399 once invoked, about $0.0002 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 2026-09-01.
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.
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.
detect-flaky-tests
Detects flaky Go tests by analyzing GitHub Actions workflow runs across the last 7 days and all PRs — covering both the run-tests job (unit/integration) and the e2e-test job (gVisor and microVM lanes). For each newly-detected flaky test or infra issue, opens a GitHub issue with full evidence and a draft fix PR. Does…
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.