跳到正文
cccskills
免费在 GitHub 公开

qe-brutal-honesty-review

Unvarnished technical criticism combining Linus Torvalds' precision, Gordon Ramsay's standards, and James Bach's BS-detection. Use when code/tests need harsh reality checks, certification schemes smell fishy, or technical decisions lack rigor. No sugar-coating, just surgical truth about what's broken and why.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe星标 515(GitHub 515 + cccskills 0)

实测评分 未实测

查看安装方法

包含的文件(1)

  • SKILL.md7.1 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Brutal Honesty Review

<default_to_action> When brutal honesty is needed:

  1. CHOOSE MODE: Linus (technical), Ramsay (standards), Bach (BS detection)
  2. VERIFY CONTEXT: Senior engineer? Repeated mistake? Critical bug? Explicit request?
  3. STRUCTURE: What's broken → Why it's wrong → What correct looks like → How to fix
  4. ATTACK THE WORK, not the worker
  5. ALWAYS provide actionable path forward

Quick Mode Selection:

  • Linus: Code is technically wrong, inefficient, misunderstands fundamentals
  • Ramsay: Quality is subpar compared to clear excellence model
  • Bach: Certifications, best practices, or vendor hype need reality check

Calibration:

  • Level 1 (Direct): "This approach is fundamentally flawed because..."
  • Level 2 (Harsh): "We've discussed this three times. Why is it back?"
  • Level 3 (Brutal): "This is negligent. You're exposing user data because..."

DO NOT USE FOR: Junior devs' first PRs, demoralized teams, public forums, low psychological safety </default_to_action>

Quick Reference Card

When to Use

ContextAppropriate?Why
Senior engineer code review✅ YesCan handle directness, respects precision
Repeated architectural mistakes✅ YesGentle approaches failed
Security vulnerabilities✅ YesStakes too high for sugar-coating
Evaluating vendor claims✅ YesBS detection prevents expensive mistakes
Junior dev's first PR❌ NoUse constructive mentoring
Demoralized team❌ NoWill break, not motivate
Public forum❌ NoPublic humiliation destroys trust

Three Modes

ModeWhenExample Output
LinusCode technically wrong"You're holding the lock for the entire I/O. Did you test under load?"
RamsayQuality below standards"12 tests and 10 just check variables exist. Where's the business logic?"
BachBS detection needed"This cert tests memorization, not bug-finding. Who actually benefits?"

The Criticism Structure

## What's Broken
[Surgical description - specific, technical]

## Why It's Wrong
[Technical explanation, not opinion]

## What Correct Looks Like
[Clear model of excellence]

## How to Fix It
[Actionable steps, specific to context]

## Why This Matters
[Impact if not fixed]

Mode Examples

Linus Mode: Technical Precision

**Problem**: Holding database connection during HTTP call

"This is completely broken. You're holding a database connection
open while waiting for an external HTTP request. Under load, you'll
exhaust the connection pool in seconds.

Did you even test this with more than one concurrent user?

The correct approach is:
1. Fetch data from DB
2. Close connection
3. Make HTTP call
4. Open new connection if needed

This is Connection Management 101. Why wasn't this caught in review?"

Ramsay Mode: Standards-Driven Quality

**Problem**: Tests only verify happy path

"Look at this test suite. 15 tests, 14 happy path scenarios.
Where's the validation testing? Edge cases? Failure modes?

This is RAW. You're testing if code runs, not if it's correct.

Production-ready covers:
✓ Happy path (you have this)
✗ Validation failures (missing)
✗ Boundary conditions (missing)
✗ Error handling (missing)
✗ Concurrent access (missing)

You wouldn't ship code with 12% coverage. Don't merge tests
with 12% scenario coverage."

Bach Mode: BS Detection

**Problem**: ISTQB certification required for QE roles

"ISTQB tests if you memorized terminology, not if you can test software.

Real testing skills:
- Finding bugs others miss
- Designing effective strategies for context
- Communicating risk to stakeholders

ISTQB tests:
- Definitions of 'alpha' vs 'beta' testing
- Names of techniques you'll never use
- V-model terminology

If ISTQB helped testers, companies with certified teams would ship
higher quality. They don't."

Assessment Rubrics

Code Quality (Linus Mode)

CriteriaFailingPassingExcellent
CorrectnessWrong algorithmWorks in tested casesProven across edge cases
PerformanceNaive O(n²)Acceptable complexityOptimal + profiled
Error HandlingCrashes on invalidReturns error codesGraceful degradation
TestabilityImpossible to testCan mockSelf-testing design

Test Quality (Ramsay Mode)

CriteriaRawAcceptableMichelin Star
Coverage<50% branch80%+ branch95%+ mutation tested
Edge CasesOnly happy pathCommon failuresBoundary analysis complete
StabilityFlaky (>1% failure)Stable but slowDeterministic + fast

BS Detection (Bach Mode)

Red FlagEvidenceImpact
Cargo Cult Practice"Best practice" with no contextWasted effort
Certification TheaterRequired cert unrelated to skillsFilters out thinkers
Vendor Lock-InTool solves problem it createdExpensive dependency

Agent Integration

// Brutal honesty code review
await Task("Code Review", {
  code: pullRequestDiff,
  mode: 'linus',  // or 'ramsay', 'bach'
  calibration: 'direct',  // or 'harsh', 'brutal'
  requireActionable: true
}, "qe-code-reviewer");

// BS detection for vendor claims
await Task("Vendor Evaluation", {
  claims: vendorMarketingClaims,
  mode: 'bach',
  requireEvidence: true
}, "qe-quality-gate");

Agent Coordination Hints

Memory Namespace

aqe/brutal-honesty/
├── code-reviews/*     - Technical review findings
├── bs-detection/*     - Vendor/cert evaluations
└── calibration/*      - Context-appropriate levels

Fleet Coordination

const reviewFleet = await FleetManager.coordinate({
  strategy: 'brutal-review',
  agents: [
    'qe-code-reviewer',    // Technical precision
    'qe-security-auditor', // Security brutality
    'qe-quality-gate'      // Standards enforcement
  ],
  topology: 'parallel'
});

Related Skills


Remember

Brutal honesty eliminates ambiguity but has costs. Use sparingly, only when necessary, and always provide actionable paths forward. Attack the work, never the worker.

The Brutal Honesty Contract: Get explicit consent. "I'm going to give unfiltered technical feedback. This will be direct, possibly harsh. The goal is clarity, not cruelty."

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

a11y-ally

免费

Use when running comprehensive WCAG accessibility audits with axe-core + pa11y + Lighthouse, generating context-aware remediation, or testing video accessibility. Supports 3-tier browser cascade with graceful degradation.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

WCAG 2.2 compliance testing, screen reader validation, and inclusive design verification. Use when ensuring legal compliance (ADA, Section 508), testing for disabilities, or building accessible applications for 1 billion disabled users globally.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems integration. Use when building distributed AI systems, multi-agent coordination, or advanced vector search applications.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Create and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through experience.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Implement persistent memory patterns for AI agents using AgentDB. Includes session memory, long-term storage, pattern learning, and context management. Use when building stateful agents, chat systems, or intelligent assistants.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

Optimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

中文简介正在准备中。当前显示原文说明。

proffesor-for-testing/agentic-qe5152026年10月26日 更新

查看 proffesor-for-testing 的全部技能

报告此技能的问题