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Agent Skill · 研究检索

code-qc(质量控制代码)

code-qc 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

code-qc 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为需要联网;许可证为 MIT-0,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 5,810。

总安装 24,286周安装 973GitHub Stars 公开资料未说明下载 7,862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
MIT-0
版本
1.0.0

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-qc(质量控制代码)
来源仓库:https://github.com/isonaei/code-qc
安装命令:
openclaw skills install code-qc
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install code-qc

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。

对代码库运行结构化质量控制审计,支持多种主流编程语言。适用于定期质量检查、安全审计或合规性验证任务。输出可操作的改进建议,覆盖错误处理、性能和安全方面。扫描结果不能直接作为最终结论,需人工复核确认。使用前应确保有足够权限访问目标仓库和依赖项。code-qc 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

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 OpenClaw;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 openclaw skills install code-qc;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-qc 怎么安装?

在终端执行 openclaw skills install code-qc。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

code-qc 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。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-qc 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-qc 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

code-qc 用的人多吗?

公开数据是累计安装 24,286 次,近一周安装 973 次,下载 7,862 次。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-qc 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。

先想清楚的地方

  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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 OpenClaw,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-qc

质量控制代码 · 本页

24,286—需要联网MIT-0有提醒

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

name
code-qc
description
Run a structured quality control audit on any codebase. Use when asked to QC, audit, review, or check code quality for a project. Supports Python, TypeScript, GDScript, and general projects. Produces a standardized report with PASS/WARN/FAIL verdict, covering tests, imports, type checking, static analysis, smoke tests, and documentation. Also use when asked to compare QC results over time.

Code QC

Structured quality control audit for codebases. Delegates static analysis to proper tools (ruff, eslint, gdlint) and focuses on what AI adds: semantic understanding, cross-module consistency, and dynamic smoke test generation.

Quick Start

  1. Detect project type (read the profile for that language)
  2. Load .qc-config.yaml if present (for custom thresholds/exclusions)
  3. Run the 8-phase audit (or subset with --quick)
  4. Generate report with verdict
  5. Save baseline for future comparison

Configuration (.qc-config.yaml)

Optional project-level config for monorepos and custom settings:

# .qc-config.yaml
thresholds:
  test_failure_rate: 0.05    # >5% = FAIL, 0-5% = WARN, 0% = PASS
  lint_errors_max: 0         # Max lint errors before FAIL
  lint_warnings_max: 50      # Max warnings before WARN
  type_errors_max: 0         # Max type errors before FAIL (strict by default)

exclude:
  dirs: [vendor, third_party, generated]
  files: ["*_generated.py", "*.pb.go"]

changed_only: false          # Only check git-changed files (CI mode)
fail_fast: false             # Stop on first failure
quick_mode: false            # Only run Phase 1, 3, 3.5, 6

languages:
  python:
    min_coverage: 80
    ignore_rules: [T201]     # Allow print in this project
  typescript:
    strict_mode: true        # Require tsconfig strict: true
    ignore_rules: []         # eslint rules to ignore
  gdscript:
    godot_version: "4.2"

Execution Modes

ModePhases RunUse Case
Full (default)All 8 phasesThorough audit
--quick1, 3, 3.5, 6Fast sanity check
--changed-onlyAll, filteredCI on pull requests
--fail-fastAll, stops earlyFind first issue fast
--fix3 with autofixApply automatic fixes

Phase Overview

#PhaseWhatTools
1Test SuiteRun existing tests + coveragepytest --cov / jest --coverage
2Import IntegrityVerify all modules loadscripts/import_check.py
3Static AnalysisLint with proper toolsruff / eslint / gdlint
3.5Type CheckingStatic type verificationmypy / tsc --noEmit / (N/A for GDScript)
4Smoke TestsVerify business logic worksAI-generated per project
5UI/FrontendVerify UI components loadFramework-specific
6File ConsistencySyntax + git statescripts/syntax_check.py + git
7DocumentationDocstrings + docs accuracyscripts/docstring_check.py

Phase Details

Phase 1: Test Suite

Run the project's test suite with coverage. Auto-detect the test runner:

pytest.ini / pyproject.toml [tool.pytest] → pytest --cov
package.json scripts.test → npm test (or npx vitest --coverage)
Cargo.toml → cargo test
project.godot → (GUT if present, else manual)

Record: total, passed, failed, errors, skipped, duration, coverage %.

Verdict contribution:

  • No tests found → SKIP (not FAIL; project may be config-only)
  • Failure rate = 0% → PASS
  • Failure rate ≤ threshold (default 5%) → WARN
  • Failure rate > threshold → FAIL

Coverage reporting (Python):

pytest --cov=<package> --cov-report=term-missing --cov-report=json

Phase 2: Import Integrity (Python/GDScript)

Python: Run scripts/import_check.py against the project root.

GDScript: Verify scene/preload references are valid (see gdscript-profile.md).

Critical vs Optional Import Classification

Use these heuristics to classify import failures:

PatternClassificationRationale
__init__.py, main.py, app.py, cli.pyCriticalCore entry points
Module in src/, lib/, or top-level packageCriticalCore functionality
*_test.py, test_*.py, conftest.pyOptionalTest infrastructure
Modules in examples/, scripts/, tools/OptionalAuxiliary code
Import error mentions cuml, triton, tensorrtOptionalHardware-specific
Import error mentions missing system libOptionalEnvironment-specific
Dependency in [project.optional-dependencies]OptionalDeclared optional

Phase 3: Static Analysis

Do NOT use grep. Use the language's standard linter.

Standard Mode
# Python
ruff check --select E722,T201,B006,F401,F841,UP,I --statistics <project>

# TypeScript  
npx eslint . --format json

# GDScript
gdlint <project>
Fix Mode (--fix)

When --fix is specified, apply automatic corrections:

# Python — safe auto-fixes
ruff check --fix --select E,F,I,UP <project>
ruff format <project>

# TypeScript
npx eslint . --fix

# GDScript
gdformat <project>

Important: After --fix, re-run the check to report remaining issues that couldn't be auto-fixed.

Phase 3.5: Type Checking (NEW)

Run static type analysis before proceeding to runtime checks.

Python:

mypy <package> --ignore-missing-imports --no-error-summary
# or if pyproject.toml has [tool.pyright]:
pyright <package>

TypeScript:

npx tsc --noEmit

GDScript: Godot 4 has built-in static typing but no standalone checker. Estimate type coverage manually:

# Find untyped declarations
grep -rn "var \w\+ =" --include="*.gd" .       # Untyped variables
grep -rn "func \w\+(" --include="*.gd" . | grep -v ":"  # Untyped functions

Use the estimate_type_coverage() function from gdscript-profile.md to calculate coverage per file:

# From gdscript-profile.md
def estimate_type_coverage(gd_file: str) -> float:
    """Count typed vs untyped declarations."""
    # See full implementation in gdscript-profile.md

Also check for @warning_ignore annotations which may hide type issues.

Record: Total errors, categorized by severity.

Phase 4: Smoke Tests (Business Logic)

Test backend/core functionality — NOT UI components (that's Phase 5).

API Discovery Heuristics:

  1. Entry points: Look for main(), cli(), app, create_app(), __main__.py
  2. Service layer: Find classes/modules named *Service, *Manager, *Handler
  3. Public API: Check __all__ exports in __init__.py
  4. FastAPI/Flask: Find route decorators (@app.get, @router.post)
  5. CLI: Find typer/click @app.command() decorators
  6. SDK: Look for client classes, public methods without _ prefix

For each discovered API, generate a minimal test:

def smoke_test_user_service():
    """Test UserService basic CRUD."""
    from myproject.services.user import UserService
    svc = UserService(db=":memory:")
    user = svc.create(name="test")
    assert user.id is not None
    fetched = svc.get(user.id)
    assert fetched.name == "test"
    return "PASS"

Guidelines:

  • Import + instantiate + call one method with minimal valid input
  • Use in-memory/temp resources (:memory:, tempdir)
  • Each test < 5 seconds
  • Catch exceptions, report clearly

Phase 5: UI/Frontend Verification

Test UI components separately from business logic.

FrameworkTest Method
Gradiofrom project.ui import create_ui (no launch())
Streamlitstreamlit run app.py --headless exits cleanly
PyQt/PySideSet QT_QPA_PLATFORM=offscreen, import widget modules
Reactnpm run build succeeds
Vuenpm run build succeeds
GodotScene files parse without error, required scripts exist
CLI--help on all subcommands returns 0

Boundary: Phase 4 tests "does the logic work?" Phase 5 tests "does the UI render?"

Phase 6: File Consistency

Run scripts/syntax_check.py — compiles all source files to verify no syntax errors.

Note: Phase 2 (Import Integrity) tests *runtime* import behavior including initialization code. Phase 6 tests *static* syntax correctness. Both are needed: a file can have valid syntax but fail to import (e.g., missing dependency), or vice versa (syntax error in a module that's never imported).

Check git state:

git status --short      # Should be clean (or report uncommitted changes)
git diff --check        # No conflict markers

Phase 7: Documentation

Run scripts/docstring_check.py (now checks __init__.py by default).

Also verify:

  • README exists and is non-empty
  • Key docs (CHANGELOG, CONTRIBUTING) exist if referenced
  • No stale TODO markers in docs claiming completion

Verdict Logic

# Calculate test failure rate
failure_rate = test_failures / total_tests

# Default thresholds (override in .qc-config.yaml)
FAIL_THRESHOLD = 0.05  # 5%
WARN_THRESHOLD = 0.00  # 0%
TYPE_ERRORS_MAX = 0    # Default: strict (any type error = FAIL)

# Verdict determination
if any([
    failure_rate > FAIL_THRESHOLD,
    critical_import_failure,
    type_check_errors > thresholds.type_errors_max,  # Configurable threshold
    lint_errors > thresholds.lint_errors_max,
]):
    verdict = "FAIL"
elif any([
    0 < failure_rate <= FAIL_THRESHOLD,
    optional_import_failures > 0,
    lint_warnings > thresholds.lint_warnings_max,
    missing_docstrings > 0,
    smoke_test_failures > 0,
]):
    verdict = "PASS WITH WARNINGS"
else:
    verdict = "PASS"

Baseline Comparison

Save results to .qc-baseline.json:

{
  "timestamp": "2026-02-15T15:00:00Z",
  "commit": "abc123",
  "verdict": "PASS WITH WARNINGS",
  "config": {
    "mode": "full",
    "thresholds": {"test_failure_rate": 0.05}
  },
  "phases": {
    "tests": {"total": 134, "passed": 134, "failed": 0, "coverage": 87.5},
    "imports": {"total": 50, "failed": 0, "optional_failed": 1, "critical_failed": 0},
    "types": {"errors": 0, "warnings": 5},
    "lint": {"errors": 0, "warnings": 12, "fixed": 8},
    "smoke": {"total": 14, "passed": 14},
    "docs": {"missing_docstrings": 3}
  }
}

On subsequent runs, report delta:

Tests:      134 → 140 (+6 ✅)
Coverage:   87% → 91% (+4% ✅)
Type errors: 0 → 0 (✅)
Lint warnings: 12 → 5 (-7 ✅)

Report Output

Generate in 3 formats:

  1. Markdown (qc-report.md) — full detailed report for humans
  2. JSON (.qc-baseline.json) — machine-readable for CI/comparison
  3. Summary (chat message) — 10-line digest for Discord/Slack

Summary Format Example

📊 QC Report: my-project @ abc123
Verdict: ✅ PASS WITH WARNINGS

Tests:    134/134 passed (100%) | Coverage: 87%
Types:    0 errors
Lint:     0 errors, 12 warnings
Imports:  50/50 (1 optional failed)
Smoke:    14/14 passed

⚠️ Warnings:
- 3 missing docstrings
- 12 lint warnings (run with --fix)

Language-Specific Profiles

Read the appropriate profile before running:

  • Python: references/python-profile.md
  • TypeScript: references/typescript-profile.md
  • GDScript: references/gdscript-profile.md
  • General (any language): references/general-profile.md

平台分布

OpenClaw

98.24%
按下载量换算7,724

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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