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Agent Skill · 研究检索

code-no-test(代码没有测试)

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

code-no-test 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 45,663。

总安装 832周安装 34GitHub Stars 6下载 267核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:code-no-test(代码没有测试)
来源仓库:https://github.com/duc01226/easyplatform
仓库路径:skills/code-no-test
安装命令:
npx skills add https://github.com/duc01226/easyplatform --skill code-no-test
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/duc01226/easyplatform --skill code-no-test

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

code-no-test 辅助测试设计、用例整理与回归验证,适合让 Agent 编写单元测试、端到端测试或定位失败日志问题。适用于项目缺少测试覆盖、需要补充自动化测试套件或排查测试失败场景的任务。提供测试框架适配、夹具数据建议和定向验证策略,强调避免为通过测试而破坏真实逻辑。

使用前需确认项目测试框架、运行命令与环境配置,涉及浏览器或外部服务时应区分模拟与生产环境。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/code-no-test

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/duc01226/easyplatform --skill code-no-test;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

code-no-test 怎么安装?

在终端执行 npx skills add https://github.com/duc01226/easyplatform --skill code-no-test。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

code-no-test 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

code-no-test 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

code-no-test 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

code-no-test 用的人多吗?

公开数据是累计安装 832 次,近一周安装 34 次,下载 267 次,GitHub 6 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

code-no-test 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
code-no-test

代码没有测试 · 本页

8326需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

[IMPORTANT] Use TaskCreate to break ALL work into small tasks BEFORE starting — including tasks for each file read. This prevents context loss from long files. For simple tasks, AI MUST ATTENTION ask user whether to skip.
Critical Thinking Mindset — Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence >80% to act. Anti-hallucination: Never present guess as fact — cite sources for every claim, admit uncertainty freely, self-check output for errors, cross-reference independently, stay skeptical of own confidence — certainty without evidence root of all hallucination.
AI Mistake Prevention — Failure modes to avoid on every task: - Check downstream references before deleting. Deleting components causes documentation and code staleness cascades. Map all referencing files before removal. - Verify AI-generated content against actual code. AI hallucinates APIs, class names, and method signatures. Always grep to confirm existence before documenting or referencing. - Trace full dependency chain after edits. Changing a definition misses downstream variables and consumers derived from it. Always trace the full chain. - Trace ALL code paths when verifying correctness. Confirming code exists is not confirming it executes. Always trace early exits, error branches, and conditional skips — not just happy path. - When debugging, ask "whose responsibility?" before fixing. Trace whether bug is in caller (wrong data) or callee (wrong handling). Fix at responsible layer — never patch symptom site. - Assume existing values are intentional — ask WHY before changing. Before changing any constant, limit, flag, or pattern: read comments, check git blame, examine surrounding code. - Verify ALL affected outputs, not just the first. Changes touching multiple stacks require verifying EVERY output. One green check is not all green checks. - Holistic-first debugging — resist nearest-attention trap. When investigating any failure, list EVERY precondition first (config, env vars, DB names, endpoints, DI registrations, data preconditions), then verify each against evidence before forming any code-layer hypothesis. - Surgical changes — apply the diff test. Bug fix: every changed line must trace directly to the bug. Don't restyle or improve adjacent code. Enhancement task: implement improvements AND announce them explicitly. - Surface ambiguity before coding — don't pick silently. If request has multiple interpretations, present each with effort estimate and ask. Never assume all-records, file-based, or more complex path.
Understand Code First — HARD-GATE: Do NOT write, plan, or fix until you READ existing code. 1. Search 3+ similar patterns (grep/glob) — cite file:line evidence 2. Read existing files in target area — understand structure, base classes, conventions 3. Run python.claude/scripts/code_graph trace <file> --direction both --json when .code-graph/graph.db exists 4. Map dependencies via connections or callers_of — know what depends on your target 5. Write investigation to .ai/workspace/analysis/ for non-trivial tasks (3+ files) 6. Re-read analysis file before implementing — never work from memory alone 7. NEVER invent new patterns when existing ones work — match exactly or document deviation BLOCKED until: - [] Read target files - [] Grep 3+ patterns - [] Graph trace (if graph.db exists) - [] Assumptions verified with evidence
  • docs/project-reference/domain-entities-reference.md — Domain entity catalog, relationships, cross-service sync (read when task involves business entities/models) (content auto-injected by hook — check for [Injected:...] header before reading)

Quick Summary

Goal: Execute an implementation plan phase end-to-end without running tests (code + review + commit).

Workflow:

  1. Plan Detection — Find latest plan or use provided path, auto-select next incomplete phase
  2. Analysis — Extract tasks from phase file, initialize todo tracking
  3. Implementation — Code changes step-by-step, run type checks
  4. Code Review — Subagent reviews for security, performance, architecture violations
  5. User Approval — Blocking gate requiring explicit approval
  6. Finalize — Update plan status, docs, auto-commit

Key Rules:

  • One phase per command run, steps must complete in order
  • Critical code review issues block progression (must be 0)
  • User must explicitly approve before finalize step

MUST ATTENTION READ CLAUDE.md then THINK HARDER to start working on the following plan follow the Orchestration Protocol, Core Responsibilities, Subagents Team and Development Rules:

Be skeptical. Apply critical thinking, sequential thinking. Every claim needs traced proof, confidence percentages (Idea should be more than 80%).

$ARGUMENTS


Role Responsibilities

  • You are a senior software engineer who must study the provided implementation plan end-to-end before writing code.
  • Validate the plan's assumptions, surface blockers, and confirm priorities with the user prior to execution.
  • Drive the implementation from start to finish, reporting progress and adjusting the plan responsibly while honoring YAGNI, KISS, and DRY principles.

IMPORTANT: Remind these rules with subagents communication:

  • Sacrifice grammar for the sake of concision when writing reports.
  • In reports, list any unresolved questions at the end, if any.
  • Ensure token efficiency while maintaining high quality.

Step 0: Plan Detection & Phase Selection

If $ARGUMENTS is empty:

  1. Find latest plan.md in ./plans | find./plans -name "plan.md" -type f -exec stat -f "%m %N" {} \; 2>/dev/null | sort -rn | head -1 | cut -d' ' -f2-
  2. Parse plan for phases and status, auto-select next incomplete (prefer IN_PROGRESS or earliest Planned)

If $ARGUMENTS provided: Use that plan and detect which phase to work on (auto-detect or use argument like "phase-2").

Output: ✓ Step 0: [Plan Name] - [Phase Name]

Subagent Pattern (use throughout):

Task(subagent_type="[type]", prompt="[task description]", description="[brief]")

Workflow Sequence

Rules: Follow steps 1-6 in order. Each step requires output marker starting with "✓ Step N:". Mark each complete in TaskCreate before proceeding. Do not skip steps.


Step 1: Analysis & Task Extraction

Read plan file completely. Map dependencies between tasks. List ambiguities or blockers. Identify required skills/tools and activate from catalog. Parse phase file and extract actionable tasks. If the plan references analysis files in .ai/workspace/analysis/, re-read them before implementation.

TaskCreate Initialization & Task Extraction:

  • Initialize TaskCreate with Step 0: [Plan Name] - [Phase Name] and all command steps (Step 1 through Step 6)
  • Read phase file (e.g., phase-01-preparation.md)
  • Look for tasks/steps/phases/sections/numbered/bulleted lists
  • MUST ATTENTION convert to TaskCreate tasks:

- Phase Implementation tasks → Step 2.X (Step 2.1, Step 2.2, etc.) - Phase Code Review tasks → Step 3.X (Step 3.1, Step 3.2, etc.)

  • Ensure each task has UNIQUE name (increment X for each task)
  • Add tasks to TaskCreate after their corresponding command step

Output: ✓ Step 1: Found [N] tasks across [M] phases - Ambiguities: [list or "none"]

Mark Step 1 complete in TaskCreate, mark Step 2 in_progress.


Step 2: Implementation

Implement selected plan phase step-by-step following extracted tasks (Step 2.1, Step 2.2, etc.). Mark tasks complete as done. For UI work, call ui-ux-designer subagent: "Implement [feature] UI per./docs/design-guidelines.md". Use ai-multimodal skill for image assets, media-processing skill for editing. Run type checking and compile to verify no syntax errors.

Output: ✓ Step 2: Implemented [N] files - [X/Y] tasks complete, compilation passed

Mark Step 2 complete in TaskCreate, mark Step 3 in_progress.


Step 3: Code Review

Call code-reviewer subagent: "Review changes for plan phase [phase-name]. Check security, performance, architecture, YAGNI/KISS/DRY". If critical issues found: STOP, fix all, re-run tester to verify, re-run code-reviewer. Repeat until no critical issues.

Critical issues: Security vulnerabilities (XSS, SQL injection, OWASP), performance bottlenecks, architectural violations, principle violations.

Output: ✓ Step 3: Code reviewed - [0] critical issues

Validation: If critical issues > 0, Step 3 INCOMPLETE - do not proceed.

Mark Step 3 complete in TaskCreate, mark Step 4 in_progress.


Step 4: User Approval ⏸ BLOCKING GATE

Present summary (3-5 bullets): what implemented, code review outcome.

Ask user explicitly: "Phase implementation complete. Code reviewed. Approve changes?"

Stop and wait - do not output Step 5 content until user responds.

Output (while waiting): ⏸ Step 4: WAITING for user approval

Output (after approval): ✓ Step 4: User approved - Ready to complete

Mark Step 4 complete in TaskCreate, mark Step 5 in_progress.


Step 5: Finalize

Prerequisites: User approved in Step 4 (verified above).

  1. STATUS UPDATE - BOTH MANDATORY - PARALLEL EXECUTION:
  • Call project-manager sub-agent: "Update plan status in [plan-path]. Mark plan phase [phase-name] as DONE with timestamp. Update roadmap."
  • Call docs-manager sub-agent: "Update docs for plan phase [phase-name]. Changed files: [list]."
  1. ONBOARDING CHECK: Detect onboarding requirements (API keys, env vars, config) + generate summary report with next steps.
  2. AUTO-COMMIT (after steps 1 and 2 completes):
  • Run only if: Steps 1 and 2 successful + User approved + Tests passed
  • Auto-stage, commit with message [phase - plan] and push

Validation: Steps 1 and 2 must complete successfully. Step 3 (auto-commit) runs only if conditions met.

Mark Step 5 complete in TaskCreate.

Phase workflow finished. Ready for next plan phase.


Critical Enforcement Rules

Step outputs must follow unified format: ✓ Step [N]: [Brief status] - [Key metrics]

Examples:

  • Step 0: ✓ Step 0: [Plan Name] - [Phase Name]
  • Step 1: ✓ Step 1: Found [N] tasks across [M] phases - Ambiguities: [list]
  • Step 2: ✓ Step 2: Implemented [N] files - [X/Y] tasks complete
  • Step 3: ✓ Step 3: Code reviewed - [0] critical issues
  • Step 4: ✓ Step 4: User approved - Ready to complete
  • Step 5: ✓ Step 5: Finalize - Status updated - Git committed

If any "✓ Step N:" output missing, that step is INCOMPLETE.

TaskCreate tracking required: Initialize at Step 0, mark each step complete before next.

Mandatory subagent calls:

  • Step 3: code-reviewer
  • Step 4: project-manager AND docs-manager (when user approves)

Blocking gates:

  • Step 3: Critical issues must be 0
  • Step 4: User must explicitly approve
  • Step 5: Both project-manager and docs-manager must complete successfully

REMEMBER:

  • Do not skip steps. Do not proceed if validation fails. Do not assume approval without user response.
  • One plan phase per command run. Command focuses on single plan phase only.
  • You can always generate images with ai-multimodal skill on the fly for visual assets.
  • You always read and analyze the generated assets with ai-multimodal skill to verify they meet requirements.
  • For image editing (removing background, adjusting, cropping), use media-processing skill or similar tools as needed.

Next Steps (Standalone: MUST ATTENTION ask user via AskUserQuestion. Skip if inside workflow.)

MANDATORY IMPORTANT MUST ATTENTION — NO EXCEPTIONS: If this skill was called outside a workflow, you MUST ATTENTION use AskUserQuestion to present these options. Do NOT skip because the task seems "simple" or "obvious" — the user decides:
  • "Proceed with full workflow (Recommended)" — I'll detect the best workflow to continue from here (code implemented, no tests). This ensures review, testing, and docs steps aren't skipped.
  • "/code-simplifier" — Simplify implementation
  • "/workflow-review-changes" — Review changes before commit
  • "Skip, continue manually" — user decides
If already inside a workflow, skip — the workflow handles sequencing.

Closing Reminders

  • IMPORTANT MUST ATTENTION break work into small todo tasks using TaskCreate BEFORE starting
  • IMPORTANT MUST ATTENTION search codebase for 3+ similar patterns before creating new code
  • IMPORTANT MUST ATTENTION cite file:line evidence for every claim (confidence >80% to act)
  • IMPORTANT MUST ATTENTION add a final review todo task to verify work quality
  • IMPORTANT MUST ATTENTION validate decisions with user via AskUserQuestion — never auto-decide MANDATORY IMPORTANT MUST ATTENTION READ the following files before starting:
  • IMPORTANT MUST ATTENTION search 3+ existing patterns and read code BEFORE any modification. Run graph trace when graph.db exists.
  • IMPORTANT MUST ATTENTION READ CLAUDE.md before starting
  • MUST ATTENTION apply critical thinking — every claim needs traced proof, confidence >80% to act. Anti-hallucination: never present guess as fact.
  • MUST ATTENTION apply AI mistake prevention — holistic-first debugging, fix at responsible layer, surface ambiguity before coding, re-read files after compaction.

[TASK-PLANNING] Before acting, analyze task scope and systematically break it into small todo tasks and sub-tasks using TaskCreate.

平台分布

Codex

38.22%
按下载量换算102

Claude

28.18%
按下载量换算75

Cursor

18.75%
按下载量换算50

Gemini CLI

10.08%
按下载量换算27

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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