feat(configs): add code_reviewer skill and coding_harness pipeline

- code_reviewer.yaml: Verifier Agent skill config for adversarial review
  with structured output schema for ReviewFeedback format
- coding_harness.yaml: Example pipeline with adversarial loop
  develop → test → review (Worker↔Verifier) → archive
This commit is contained in:
chiguyong 2026-06-12 09:38:37 +08:00
parent dc07c7c60a
commit 6731d96c65
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name: coding_harness
version: "1.0"
description: "Coding pipeline with adversarial review loop - Worker ↔ Verifier 对抗闭环"
stages:
# 阶段 1Developer 编写代码
- name: develop
agent: developer_agent
action: implement_feature
outputs:
- code
- test_files
timeout_seconds: 600
retry_count: 1
# 阶段 2Tester 运行测试
- name: test
agent: tester_agent
action: run_tests
depends_on:
- develop
inputs:
code: "${develop.code}"
test_files: "${develop.test_files}"
outputs:
- test_results
timeout_seconds: 300
retry_count: 2
# 阶段 3代码审查对抗模式
# Worker (developer_agent) 产出 → Verifier (code_reviewer) 审查 → 不通过则打回修复
- name: review
agent: developer_agent
action: fix_code_issues
verifier: code_reviewer
depends_on:
- test
max_adversarial_rounds: 3
feedback_mode: "structured+natural"
escalate_on_exhaust: human_approval
inputs:
code: "${develop.code}"
test_results: "${test.test_results}"
outputs:
- final_code
- review_report
timeout_seconds: 900
# 阶段 4归档提交
- name: archive
agent: archiver_agent
action: commit_and_push
depends_on:
- review
inputs:
code: "${review.final_code}"
timeout_seconds: 120
continue_on_failure: false
variables:
target_branch: main
require_approval: true
commit_message_prefix: "feat"

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name: code_reviewer
agent_type: dynamic_tool_chain
version: "1.0.0"
description: "代码审查 Verifier Agent用于对抗闭环中的质量门禁"
task_mode: llm_generate
execution_mode: direct
max_concurrency: 5
intent:
keywords: ["review", "审查", "code review", "代码审查"]
description: "代码质量审查、逻辑检查、安全漏洞检测"
examples:
- "Review this code for quality"
- "审查这段代码"
- "Check for security vulnerabilities"
capabilities:
- code_review
- quality_verification
- structured_feedback
prompt:
identity: "You are a strict code reviewer specializing in quality assessment."
instructions: |
Review the provided code output for:
1. **Logic correctness** - edge cases, error handling, boundary conditions
2. **Security vulnerabilities** - injection risks, authentication bypass, data exposure
3. **Architecture and design** - separation of concerns, design patterns, coupling
4. **Test coverage** - are tests comprehensive, do they cover edge cases
5. **Code style and readability** - naming conventions, documentation, complexity
Return a STRICT structured review in this exact JSON format:
{
"passed": true/false,
"score": 0.0-1.0,
"summary": "Brief natural language summary of review findings",
"issues": [
{
"severity": "critical|major|minor",
"category": "logic_error|security|style|test_failure|architecture",
"description": "Clear description of the issue",
"location": "file:line if applicable",
"suggestion": "How to fix this issue"
}
]
}
Be thorough and specific. If there are no issues, set passed=true and issues=[].
llm:
model: "default"
temperature: 0.1
max_tokens: 2048
tools:
- shell
quality_gate:
required_fields: ["passed", "issues", "summary", "score"]
max_retries: 0
output_schema:
type: object
required:
- passed
- score
- summary
- issues
properties:
passed:
type: boolean
score:
type: number
minimum: 0
maximum: 1
summary:
type: string
minLength: 10
issues:
type: array
items:
type: object
required:
- severity
- category
- description
properties:
severity:
type: string
enum: ["critical", "major", "minor"]
category:
type: string
enum: ["logic_error", "security", "style", "test_failure", "architecture"]
description:
type: string
minLength: 10
location:
type: string
suggestion:
type: string