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tailtest-cline

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tailtest-cline

你负责构建，我们负责覆盖。同时支持 8 种以上的编辑器。

tailtest-cline 是一个 Cline 插件，每当代理编辑源文件时，它都会自动生成并运行测试。它与其它 tailtest 变体使用相同的 R1-R15 规则层。对抗性测试模式 (V13) 从第一天起就已发布。

Cline 支持范围： VS Code、Cursor、JetBrains IDE、Antigravity、Zed、Neovim、VSCodium、Windsurf 以及 Cline CLI。一个插件，支持八种以上编辑器。

完整文档请见 tailtest.com/docs/cline

与其他变体有何不同

Cline 没有钩子（如 Claude Code 的 PostToolUse、Cursor 的 afterFileEdit、Codex 的 Stop）。相反，tailtest-cline 使用了三个 Cline 原生原语：

  • .clinerules/ 承载规则层（R1-R14 + R15 对抗模式）

  • tailtest-mcp 服务器（本仓库）为代理提供结构化工具：tailtest_setup、tailtest_scenario_plan、tailtest_classify_failures、tailtest_pick_template、tailtest_ping

  • 内存库 (tailtestContext.md) 在 Cline 会话中保存每个项目的配置文件

确定性策略（深度层级、R15 对抗计数、框架模板、文件路径）存在于 MCP 服务器代码中，而不是规则文本中。代理在需要脚手架时会调用这些工具，而不是在长时间的会话中依赖规则记忆。

Related MCP server: OpenTester

安装

三种安装路径：

1. Cline MCP 市场（推荐；一键安装）

在 IDE 中打开 Cline 的扩展面板。搜索 tailtest。点击安装。Cline 会自动克隆、安装依赖项并在 cline_mcp_settings.json 中注册服务器。

2. 直接通过 GitHub 安装

将 https://github.com/avansaber/tailtest-cline 粘贴到 Cline 的 MCP 服务器安装对话框中。Cline 会执行相同的克隆 + 安装 + 注册流程。

3. 手动编辑 cline_mcp_settings.json

{
  "mcpServers": {
    "tailtest": {
      "command": "python",
      "args": ["-m", "src.server"],
      "cwd": "/path/to/tailtest-cline/mcp_server",
      "alwaysAllow": [
        "tailtest_ping",
        "tailtest_scenario_plan",
        "tailtest_classify_failures",
        "tailtest_pick_template"
      ]
    }
  }
}

首次运行

安装后，在 Cline 聊天中输入："set up tailtest in this project"。

Cline 会调用 tailtest_setup。该工具会检测语言/框架/运行器，写入 .clinerules/，写入 .clinerules/workflows/，初始化 memory-bank/tailtestContext.md，并初始化 .tailtest/config.json + .tailtest/session.json。幂等性：现有文件会被保留。

重要提示： Cline 不会在对话中途自动重新加载 .clinerules。请开始新的对话（或重新加载窗口）以激活。

两种操作模式

手动模式（默认）

你需要显式调用测试周期：

  • /tailtest-test <file> -- 在特定文件上运行周期

  • /tailtest hunt <file> -- 在特定文件上进行一次性对抗性测试

  • 或者使用自然语言（“测试我刚刚编辑的文件”）

每一步（文件写入、终端命令、MCP 调用）都会提示确认。对于初次使用的用户，这是更安全的默认设置。

自动模式（可选）

为以下操作启用 Cline 自动批准：编辑文件（工作区）、执行安全命令、使用 MCP 服务器。然后运行 /tailtest-mode auto 并重新加载。每次编辑后，tailtest 都会自动触发测试周期。

计划/执行模式（Cline 原生 UX 奖励）

Cline 的“计划/执行”切换映射到 tailtest 的 SCENARIO PLAN（场景计划）约定：计划模式生成 SCENARIO PLAN（只读）；审查并修改；执行模式写入测试文件、运行它并应用 R12 分类。推荐用于高风险文件。

配置

.tailtest/config.json：

{
  "depth": "standard",
  "mode": "manual"
}

深度选项：

  • simple -- 2-3 个快乐路径场景

  • standard -- 5-8 个场景，包括 2 个以上的对抗性探测（默认）

  • thorough -- 10-15 个场景，包括 4 个以上的对抗性探测

  • adversarial -- 8-12 个偏向于破坏的场景

查看 tailtest.com/docs/config 获取所有选项，查看 tailtest.com/docs/adversarial 获取对抗模式详情。

其他 tailtest 变体

相同的 R1-R15 规则层，相同的对抗性测试模式，不同的宿主集成。本仓库是 Cline 变体。

查看 tailtest.com/demo/cline 获取此变体的实时演练，或查看 tailtest.com/comparison 获取所有四种变体的功能矩阵。

许可证

MIT。

Available Tools

5 tools
tailtest_classify_failuresA

Parse runner output (pytest, jest, etc.) into structured failure records and apply heuristic R12 classification. Returns failures with type (real_bug / environment / test_bug / unknown), reason, test name, file, line, error type, message, and a summary count per R12 category. The agent verifies or overrides the heuristic when context warrants.

ParametersJSON Schema
NameRequiredDescriptionDefault
runner_outputYesStdout (and optionally stderr) from the test runner.
runnerNoRunner name. Defaults to pytest.

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description must fully disclose behavior. It details the return fields (type, reason, test name, etc.) and mentions the agent can verify/override. It does not mention side effects, which seems acceptable for a read-only classification. Could note that no state is modified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, each adding essential information: what it does, what it returns, and how the agent interacts. No unnecessary words, front-loaded with the main action. Highly concise and well-structured.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Without an output schema, the description fully covers the return value details (fields and categories). It explains the heuristic and agent override capability. No gaps are apparent for the tool's complexity. Enough for an agent to correctly invoke and interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% with clear descriptions for both parameters. The description confirms the 'runner' parameter defaults to pytest, which is already in the schema. It does not add significant new meaning beyond the schema, but it does tie parameters to the overall classification context, earning a baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: parsing runner output and applying heuristic R12 classification. It specifies the exact resources (runner output, runner) and outputs (failure types, categories). The tool distinguishes well from siblings (none involve classification).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context: use when you have test runner output to classify. It does not explicitly exclude scenarios or name alternatives, but sibling tools are clearly different (template, ping, plan, setup), so confusion is low. A brief 'when not to use' would improve it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tailtest_pick_templateA

Return the full framework R2 template for a given source file: language baseline scenarios, framework baseline scenarios, framework-specific test pattern (e.g., NestJS Test.createTestingModule, Spring @WebMvcTest, Flask test_client), and test file path pattern. Returns just language baseline when no framework matches.

ParametersJSON Schema
NameRequiredDescriptionDefault
file_pathYesRelative or absolute path to the source file under test.
project_rootNoProject root directory. Defaults to the current working directory.

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full responsibility. It discloses the fallback behavior ('Returns just language baseline when no framework matches') and describes the output components. However, it does not mention error conditions or side effects, but given the read-only nature, this is acceptable.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, starts with the verb 'Return', and contains zero redundant information. Every phrase contributes to understanding the tool's function.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given two parameters and no output schema, the description adequately explains the return value and the fallback. It lacks mention of error cases or supported languages, but is otherwise complete for a straightforward read tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, but the parameter descriptions are minimal. The tool description adds value by explaining that the output is determined by the file_path and project_root, and contextually connects parameters to the template resolution. This goes beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it returns a framework R2 template for a given source file, listing specific components (language baseline scenarios, framework baseline scenarios, etc.). This is a specific verb+resource and differentiates from sibling tools like tailtest_classify_failures.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for picking a template for a source file but does not explicitly state when to use this tool versus alternatives. It lacks guidance on when not to use or naming sibling tools for comparison.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tailtest_pingA

Health check. Returns server version and confirms the MCP server is reachable.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.3/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, but the description honestly discloses the read-only nature and return of server version. No hidden behaviors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single concise sentence with no redundancy, efficiently conveying the tool's purpose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple ping tool with no parameters or output schema, the description fully covers its behavior and return value.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist; schema coverage is 100%. Baseline for 0 params is 4.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states it is a health check that returns server version and confirms reachability, distinguishing it from sibling tools like classification or setup.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied as a health check, but no explicit guidance on when to use vs alternatives or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tailtest_scenario_planA

Return structured scaffolding the agent uses to write its SCENARIO PLAN: language, framework, depth, R15 adversarial count requirement, language and framework baseline scenarios, test file path, and prose instructions. The agent uses this scaffolding to compose the actual SCENARIO PLAN scenario lines.

ParametersJSON Schema
NameRequiredDescriptionDefault
file_pathYesRelative or absolute path to the source file under test.
project_rootNoProject root directory. Defaults to the current working directory.

TDQS

A4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries full behavioral burden. It details the returned content but does not disclose side effects, permissions, or whether the operation is read-only. It is adequate but lacks depth on behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two sentences, front-loaded with purpose, and efficiently lists all components without redundancy or unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description lists the fields returned but does not specify the output format (e.g., JSON structure) or address error cases. Given no output schema, the agent may need to infer the structure, but the listing is helpful.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema descriptions already cover file_path and project_root with 100% coverage. The description does not add additional meaning beyond what the schema provides, so it is at baseline.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool returns 'structured scaffolding' for writing a scenario plan, listing specific components like language, framework, depth, R15 adversarial count, baseline scenarios, test path, and instructions. It distinguishes from sibling tools by focusing on scaffolding generation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides context that the scaffolding is used before composing the actual scenario plan, but it does not explicitly exclude other uses or compare with alternatives like other tailtest tools. The usage is implied.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

tailtest_setupA

Bootstrap entry point for tailtest in a Cline project. Detects language / framework / runner, writes the .clinerules/ rule pack, writes .clinerules/workflows/ slash workflows, seeds Memory Bank with tailtestContext.md (a 7th file alongside the 6 core ones; existing files are not overwritten), and initialises .tailtest/config.json + session.json. Returns a structured report including the user-facing 'reload required' warning (Cline does not auto-reload .clinerules mid-conversation).

ParametersJSON Schema
NameRequiredDescriptionDefault
project_rootNoProject directory. Defaults to the current working directory.
modeNomanual (default): user invokes /tailtest-test after edits. auto: tailtest fires after every edit (requires Cline auto-approve).

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations exist, so the description fully carries the burden. It discloses all major effects: file creation (rules, workflows, memory bank, configs), non-overwriting of existing files, and the reload warning. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise (3-4 sentences) yet packed with information. It front-loads the main purpose and each sentence serves a clear role without redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema, the description partially explains the return value (structured report with reload warning) but omits details about report fields or structure. For a tool that modifies multiple files, this is a minor gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, but the description adds valuable context beyond the schema by explaining the implications of the mode parameter (manual vs. auto) and what triggers each. This adds semantic richness.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose as the bootstrap entry point for tailtest, listing specific actions like detecting language, writing rule packs, and initializing configs. It is distinctly different from sibling tools (classify, pick, ping, scenario plan).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage as the first step in tailtest setup, but it does not explicitly state when to use or avoid it. It provides clear context but lacks explicit exclusions or alternative tool guidance.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 5 tool updatesv1.0.1
    • First observedtailtest_classify_failures
    • First observedtailtest_pick_template
    • First observedtailtest_ping
    • First observedtailtest_scenario_plan
    • First observedtailtest_setup
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TDQS

A4.4/5.0

Scored across 5 tools

Disambiguation5/5

Each tool serves a distinct purpose: setup, health check, template selection, scenario planning, and failure classification. There is no overlap or ambiguity between them.

Naming Consistency5/5

All tools follow a consistent snake_case pattern with the prefix 'tailtest_' and a verb_noun structure (e.g., tailtest_classify_failures, tailtest_pick_template). No deviations.

Tool Count5/5

With 5 tools, the server is tightly scoped to test analysis and scaffolding. Each tool earns its place without being too few or too many for the domain.

Completeness4/5

The tools cover setup, health, template selection, scenario planning, and failure classification. While not a full test framework, it appears complete for its intended planning/analysis purpose. Minor gap: no tool for running tests or generating code.

Maintenance

ActivityInactive
ResponsivenessUnresponsive

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