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Standardmäßig ist der Prompt ausgewählt, der zuerst die Quelle prüft. Sie können zu einem direkten Befehl wechseln oder eine lokale Kopie herunterladen.
Lesen Sie SKILL.md und alle von SkillsMP angezeigten Begleitdateien, bevor Sie sich für eine Installation entscheiden.
Mit Codex oder Claude installieren Kopieren Sie diesen Prompt, fügen Sie ihn in Codex, Claude oder einen anderen Assistant ein und lassen Sie die Skill-Seite prüfen und installieren.
Ein direkter Befehl überspringt den Prüf-Prompt. Prüfen Sie die Quelle, bevor Sie ihn ausführen.
npx skills add https://github.com/microwind/ai-skills --skill markdownDer Befehl bleibt in einer Zeile. Scrollen Sie horizontal, um ihn vor dem Kopieren vollständig zu prüfen.
Sie bevorzugen eine lokale Kopie? Laden Sie die Dateien herunter, die SkillsMP derzeit vorliegen.
Basierend auf der SOC-Berufsklassifikation
SKILL.md wird angezeigt
| name | Markdown验证器 |
| description | 当验证Markdown文件时，检查文档，查找损坏链接，改进文档。发布前验证Markdown。 |
| license | MIT |
文档会静默损坏。损坏的链接、无效语法和缺失文件使文档不可用。发布前必须验证。
核心原则: 文档即代码。需要验证。好的文档管理应该完整、准确、可访问、易维护。坏的文档管理会导致信息混乱、用户体验差、维护困难。
始终:
触发短语:
❌ 损坏链接
❌ 语法错误
❌ 内容问题
❌ 格式问题
#!/usr/bin/env python3
import re
import os
import requests
import yaml
from pathlib import Path
from typing import Dict, List, Optional, Tuple, Set
from dataclasses import dataclass
from enum import Enum
from urllib.parse import urljoin, urlparse
import time
class ValidationLevel(Enum):
"""验证级别"""
ERROR = "error"
WARNING = "warning"
INFO = "info"
@dataclass
class ValidationIssue:
"""验证问题"""
level: ValidationLevel
line_number: int
column: int
message: str
suggestion: Optional[str] = None
rule: Optional[str] = None
@dataclass
class LinkInfo:
"""链接信息"""
text: str
url: str
line_number: int
column: int
link_type: str # internal, external, image, anchor
:
():
.file_path = Path(file_path)
.base_path = Path(base_path) base_path .file_path.parent
.content =
.lines = []
.issues: [ValidationIssue] = []
.links: [LinkInfo] = []
.headers: [[, , ]] = []
.validation_rules = {
: ._validate_heading_hierarchy,
: ._validate_link_format,
: ._validate_code_blocks,
: ._validate_list_structure,
: ._validate_table_format,
: ._validate_image_references
}
() -> [ValidationIssue]:
.issues.clear()
._read_file():
.issues
._parse_content()
rule_name, rule_func .validation_rules.items():
:
rule_func()
Exception e:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=,
column=,
message=,
rule=rule_name
))
._check_links()
.issues
() -> :
:
(.file_path, , encoding=) f:
.content = f.read()
.lines = .content.splitlines()
FileNotFoundError:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=,
column=,
message=
))
UnicodeDecodeError:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=,
column=,
message=
))
():
line_num, line (.lines, ):
._parse_headers(line, line_num)
._parse_links(line, line_num)
():
header_match = re.(, line)
header_match:
level = (header_match.group())
text = header_match.group().strip()
.headers.append((text, level, line_num))
():
link_pattern =
re.finditer(link_pattern, line):
text = .group()
url = .group()
column = .start() +
link_type = ._determine_link_type(url)
.links.append(LinkInfo(
text=text,
url=url,
line_number=line_num,
column=column,
link_type=link_type
))
image_pattern =
re.finditer(image_pattern, line):
alt = .group()
url = .group()
column = .start() +
.links.append(LinkInfo(
text=alt,
url=url,
line_number=line_num,
column=column,
link_type=
))
() -> :
url.startswith():
url.startswith() url.startswith():
url.startswith():
url.startswith() url url:
:
():
prev_level =
text, level, line_num .headers:
prev_level > :
level > prev_level + :
.issues.append(ValidationIssue(
level=ValidationLevel.WARNING,
line_number=line_num,
column=,
message=,
suggestion=,
rule=
))
prev_level = level
():
line_num, line (.lines, ):
open_brackets = line.count()
close_brackets = line.count()
open_parens = line.count()
close_parens = line.count()
open_brackets != close_brackets:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=line_num,
column=,
message=,
suggestion=,
rule=
))
open_parens != close_parens:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=line_num,
column=,
message=,
suggestion=,
rule=
))
empty_link_pattern =
re.search(empty_link_pattern, line):
.issues.append(ValidationIssue(
level=ValidationLevel.WARNING,
line_number=line_num,
column=,
message=,
suggestion=,
rule=
))
():
in_code_block =
code_block_start =
code_fence =
line_num, line (.lines, ):
fence_match = re.(, line)
fence_match:
current_fence = fence_match.group()
language = fence_match.group()
in_code_block:
in_code_block =
code_block_start = line_num
code_fence = current_fence
current_fence == code_fence:
in_code_block =
code_fence =
:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=line_num,
column=,
message=,
suggestion=,
rule=
))
in_code_block:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=code_block_start,
column=,
message=,
suggestion=,
rule=
))
():
list_stack = []
line_num, line (.lines, ):
stripped = line.lstrip()
list_match = re.(, stripped)
list_match:
indent = (list_match.group())
marker = list_match.group()
list_stack:
last_indent, last_marker = list_stack[-]
(marker.isdigit() last_marker.isdigit()) \
( marker.isdigit() last_marker.isdigit()):
.issues.append(ValidationIssue(
level=ValidationLevel.WARNING,
line_number=line_num,
column=indent + ,
message=,
suggestion=,
rule=
))
list_stack.append((indent, marker))
stripped line.startswith() line.startswith():
list_stack.clear()
():
in_table =
table_start =
column_count =
line_num, line (.lines, ):
line:
in_table:
in_table =
table_start = line_num
column_count = line.count() -
:
current_columns = line.count() -
current_columns != column_count:
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=line_num,
column=,
message=,
suggestion=,
rule=
))
:
in_table:
in_table =
column_count =
():
link .links:
link.link_type == :
link.url.startswith() link.url.startswith():
image_path = .base_path / link.url
image_path.exists():
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=link.line_number,
column=link.column,
message=,
suggestion=,
rule=
))
():
link .links:
link.link_type == :
._check_internal_link(link)
link.link_type == :
._check_external_link(link)
link.link_type == :
._check_anchor_link(link)
():
link.url.startswith():
target_path = .base_path / link.url[:]
link.url.startswith():
target_path = .base_path / link.url
:
target_path = .base_path / link.url
target_path.exists():
.issues.append(ValidationIssue(
level=ValidationLevel.ERROR,
line_number=link.line_number,
column=link.column,
message=,
suggestion=,
rule=
))
():
:
response = requests.head(link.url, timeout=, allow_redirects=)
response.status_code >= :
.issues.append(ValidationIssue(
level=ValidationLevel.WARNING,
line_number=link.line_number,
column=link.column,
message=,
suggestion=,
rule=
))
requests.RequestException:
.issues.append(ValidationIssue(
level=ValidationLevel.WARNING,
line_number=link.line_number,
column=link.column,
message=,
suggestion=,
rule=
))
():
anchor = link.url[:]
found =
text, level, line_num .headers:
anchor_id = text.lower()
anchor_id = re.sub(, , anchor_id)
anchor_id = re.sub(, , anchor_id)
anchor_id == anchor:
found =
found:
.issues.append(ValidationIssue(
level=ValidationLevel.WARNING,
line_number=link.line_number,
column=link.column,
message=,
suggestion=,
rule=
))
() -> :
.validate()
error_count = ([i i .issues i.level == ValidationLevel.ERROR])
warning_count = ([i i .issues i.level == ValidationLevel.WARNING])
info_count = ([i i .issues i.level == ValidationLevel.INFO])
issues_by_rule = {}
issue .issues:
rule = issue.rule
rule issues_by_rule:
issues_by_rule[rule] = []
issues_by_rule[rule].append(issue)
{
: (.file_path),
: {
: (.issues),
: error_count,
: warning_count,
: info_count,
: (.links),
: (.headers)
},
: [
{
: issue.level.value,
: issue.line_number,
: issue.column,
: issue.message,
: issue.suggestion,
: issue.rule
}
issue .issues
],
: {
rule: [
{
: issue.line_number,
: issue.column,
: issue.message,
: issue.suggestion
}
issue issues
]
rule, issues issues_by_rule.items()
},
: [
{
: link.text,
: link.url,
: link.line_number,
: link.link_type
}
link .links
],
: [
{
: text,
: level,
: line_num
}
text, level, line_num .headers
]
}
__name__ == :
argparse
parser = argparse.ArgumentParser(description=)
parser.add_argument(, =)
parser.add_argument(, =)
parser.add_argument(, =)
parser.add_argument(, choices=[, ], default=, =)
parser.add_argument(, action=, =)
args = parser.parse_args()
validator = MarkdownValidator(args.file, args.base_path)
:
report = validator.generate_report()
args. == :
args.output:
(args.output, , encoding=) f:
json.dump(report, f, indent=, ensure_ascii=)
()
:
(json.dumps(report, indent=, ensure_ascii=))
:
( * )
()
( * )
()
summary = report[]
()
()
()
()
()
()
()
level_names = {
: ,
: ,
:
}
level [, , ]:
issues = [i i report[] i[] == level]
issues:
()
issue issues:
()
issue[]:
()
()
summary[] == :
()
:
()
Exception e:
()
exit()
#!/bin/bash
# markdown-batch-checker.sh - 批量Markdown检查工具
set -e
# 配置
SCAN_DIR=${1:-"."}
OUTPUT_DIR=${2:-"markdown-reports"}
CHECK_EXTERNAL=${3:-false}
PARALLEL_JOBS=${4:-4}
LOG_FILE="markdown_batch_check.log"
# 颜色输出
RED='\033[0;31m'
GREEN='\033[0;32m'
YELLOW='\033[1;33m'
BLUE='\033[0;34m'
NC='\033[0m'
log_info() {
echo -e "${GREEN}[INFO]${NC} $1" | tee -a "$LOG_FILE"
}
log_warn() {
echo -e "${YELLOW}[WARN]${NC} $1" | tee -a "$LOG_FILE"
}
log_error() {
echo -e "${RED}[ERROR]${NC} $1" | tee -a "$LOG_FILE"
}
log_step() {
echo -e "${BLUE}[STEP]${NC} $1" | tee -a "$LOG_FILE"
}
() {
[ ! -d ];
-p
log_info
}
() {
log_step
markdown_files=()
IFS= -r -d file;
markdown_files+=()
< <(find -name - f -print0)
log_info
>
}
() {
file_path=
file_basename=$( .md)
report_file=
log_info
-v python3 &> /dev/null;
python3 markdown_validator.py --output --format json 2>>
log_error
1
[ $? -eq 0 ];
log_info
0
log_error
1
}
() {
total_files=
checked_files=0
failed_files=0
log_step
IFS= -r file_path;
(( $(jobs -r | wc -l) >= PARALLEL_JOBS ));
-n
{
check_single_file ;
>>
>>
} &
((checked_files++))
(( checked_files % == ));
log_info
<
[ -f ];
failed_files=$(grep -c || )
successful_files=$(grep -c || )
failed_files=0
successful_files=0
log_info
}
() {
log_step
summary_file=
> <<
total_files=$( -l < )
>>
[ -f ];
failed_files=$(grep -c || )
successful_files=$(grep -c || )
>>
>>
>>
total_errors=0
total_warnings=0
total_issues=0
report_file /*_report.json;
[ -f ];
-v jq &> /dev/null;
errors=$(jq -r 2>/dev/null || )
warnings=$(jq -r 2>/dev/null || )
issues=$(jq -r 2>/dev/null || )
total_errors=$((total_errors + errors))
total_warnings=$((total_warnings + warnings))
total_issues=$((total_issues + issues))
>>
>>
>>
>>
>>
[ -f ];
failed_list=$(grep | -d: -f2-)
[ -n ];
>>
| sed >>
>>
>>
>>
>>
temp_file=
>
report_file /*_report.json;
[ -f ];
file_name=$( _report.json).md
-v jq &> /dev/null;
errors=$(jq -r 2>/dev/null || )
warnings=$(jq -r 2>/dev/null || )
issues=$(jq -r 2>/dev/null || )
>>
[ -f ];
-t -k4 -nr | -10 | IFS= -r file errors warnings issues;
>>
>>
>>
>>
>>
>>
>>
log_info
}
() {
log_info
-f
-f
}
() {
log_info
log_info
log_info
create_output_dir
total_files=$(find_markdown_files)
[ -eq 0 ];
log_warn
0
failed_count=0
check_files_parallel
failed_count=$?
generate_summary_report
cleanup
[ -eq 0 ];
log_info
0
log_warn
1
}
() {
}
[ = ] || [ = ];
show_help
0
main
#!/usr/bin/env python3
import re
import json
from pathlib import Path
from typing import Dict, List, Optional, Tuple
from dataclasses import dataclass
from collections import Counter
@dataclass
class QualityMetric:
"""质量指标"""
name: str
score: float
max_score: float
description: str
issues: List[str]
class DocumentQualityScorer:
"""文档质量评分器"""
def __init__(self, file_path: str):
self.file_path = Path(file_path)
self.content = ""
self.lines = []
self.metrics: List[QualityMetric] = []
# 评分权重
self.weights = {
'structure': 0.25,
'content': 0.30,
'links': 0.20,
'formatting': 0.15,
'readability': 0.10
}
() -> :
._read_file():
{: }
._analyze_structure()
._analyze_content()
._analyze_links()
._analyze_formatting()
._analyze_readability()
total_score = ._calculate_total_score()
{
: (.file_path),
: total_score,
: ._get_grade(total_score),
: [
{
: metric.name,
: metric.score,
: metric.max_score,
: (metric.score / metric.max_score) * ,
: metric.description,
: metric.issues
}
metric .metrics
],
: ._get_recommendations()
}
() -> :
:
(.file_path, , encoding=) f:
.content = f.read()
.lines = .content.splitlines()
:
():
issues = []
score =
max_score =
headers = ._extract_headers()
headers:
issues.append()
:
has_h1 = (level == _, level, _ headers)
has_h1:
issues.append()
:
score +=
prev_level =
hierarchy_issues =
_, level, _ headers:
prev_level > level > prev_level + :
hierarchy_issues +=
prev_level = level
hierarchy_issues == :
score +=
hierarchy_issues <= :
score +=
issues.append()
:
issues.append()
._has_toc():
score +=
:
issues.append()
(headers) >= :
score +=
:
issues.append()
word_count = (.content.split())
word_count >= :
score +=
:
issues.append()
.metrics.append(QualityMetric(
name=,
score=score,
max_score=max_score,
description=,
issues=issues
))
():
issues = []
score =
max_score =
code_blocks = ._count_code_blocks()
code_blocks > :
score +=
:
issues.append()
images = ._count_images()
images > :
score +=
:
issues.append()
tables = ._count_tables()
tables > :
score +=
:
issues.append()
lists = ._count_lists()
lists > :
score +=
:
issues.append()
._has_todo_comments():
score +=
:
issues.append()
desc_lines = ( line .lines (line.strip()) > )
total_lines = ([line line .lines line.strip()])
total_lines > desc_lines / total_lines > :
score +=
:
issues.append()
.metrics.append(QualityMetric(
name=,
score=score,
max_score=max_score,
description=,
issues=issues
))
():
issues = []
score =
max_score =
links = ._extract_links()
links:
issues.append()
.metrics.append(QualityMetric(
name=,
score=,
max_score=max_score,
description=,
issues=issues
))
(links) >= :
score +=
(links) >= :
score +=
:
issues.append()
link_types = (link.link_type link links)
(link_types) >= :
score +=
(link_types) >= :
score +=
:
issues.append()
anchor_links = [link link links link.link_type == ]
anchor_links:
score +=
:
issues.append()
external_links = [link link links link.link_type == ]
external_links:
score +=
:
issues.append()
.metrics.append(QualityMetric(
name=,
score=score,
max_score=max_score,
description=,
issues=issues
))
():
issues = []
score =
max_score =
._has_proper_code_blocks():
score +=
:
issues.append()
._has_proper_lists():
score +=
:
issues.append()
._has_proper_tables():
score +=
:
issues.append()
._has_proper_spacing():
score +=
:
issues.append()
.metrics.append(QualityMetric(
name=,
score=score,
max_score=max_score,
description=,
issues=issues
))
():
issues = []
score =
max_score =
sentences = re.split(, .content)
sentences = [s.strip() s sentences s.strip()]
sentences:
avg_sentence_length = ((s.split()) s sentences) / (sentences)
<= avg_sentence_length <= :
score +=
< avg_sentence_length <= :
score +=
issues.append()
:
issues.append()
paragraphs = [p.strip() p .content.split() p.strip()]
long_paragraphs = ( p paragraphs (p.split()) > )
long_paragraphs == :
score +=
long_paragraphs <= :
score +=
:
issues.append()
complex_words = ._count_complex_words()
total_words = (.content.split())
total_words > :
complex_ratio = complex_words / total_words
complex_ratio <= :
score +=
complex_ratio <= :
score +=
:
issues.append()
._has_excessive_repetition():
score +=
:
issues.append()
.metrics.append(QualityMetric(
name=,
score=score,
max_score=max_score,
description=,
issues=issues
))
() -> [[, , ]]:
headers = []
line_num, line (.lines, ):
= re.(, line)
:
level = (.group())
text = .group().strip()
headers.append((text, level, line_num))
headers
() -> [LinkInfo]:
links = []
line_num, line (.lines, ):
link_pattern =
re.finditer(link_pattern, line):
text = .group()
url = .group()
column = .start() +
link_type = ._determine_link_type(url)
links.append(LinkInfo(
text=text,
url=url,
line_number=line_num,
column=column,
link_type=link_type
))
image_pattern =
re.finditer(image_pattern, line):
alt = .group()
url = .group()
column = .start() +
links.append(LinkInfo(
text=alt,
url=url,
line_number=line_num,
column=column,
link_type=
))
links
() -> :
url.startswith():
url.startswith() url.startswith():
url.startswith():
:
() -> :
toc_indicators = [, , , , ]
(indicator .content indicator toc_indicators)
() -> :
todo_patterns = [, , , , ]
(re.search(pattern, .content, re.IGNORECASE) pattern todo_patterns)
() -> :
(re.findall(, .content))
() -> :
(re.findall(, .content))
() -> :
table_lines = [line line .lines line]
([line line table_lines line.strip().startswith()])
() -> :
([line line .lines re.(, line) re.(, line)])
() -> :
fences = re.findall(, .content, re.MULTILINE)
(fences) % ==
() -> :
() -> :
() -> :
header_lines = [i i, line (.lines) re.(, line)]
proper_spacing =
line_num header_lines:
line_num > .lines[line_num - ].strip() == :
proper_spacing +=
(header_lines) > proper_spacing / (header_lines) >
() -> :
words = re.findall(, .content.lower())
([word word words (word) > ])
() -> :
words = re.findall(, .content.lower())
(words) < :
word_counts = Counter(words)
most_common = word_counts.most_common()
most_common[][] / (words) >
() -> :
total_score =
total_weight =
metric .metrics:
category =
metric.name:
category =
metric.name:
category =
metric.name:
category =
metric.name:
category =
metric.name:
category =
category category .weights:
weight = .weights[category]
percentage = metric.score / metric.max_score
total_score += percentage * weight *
total_weight += weight
total_score total_weight >
() -> :
score >= :
score >= :
score >= :
score >= :
:
() -> []:
recommendations = []
metric .metrics:
metric.score < metric.max_score * :
metric.name:
recommendations.append()
metric.name:
recommendations.append()
metric.name:
recommendations.append()
metric.name:
recommendations.append()
metric.name:
recommendations.append()
recommendations
__name__ == :
argparse
parser = argparse.ArgumentParser(description=)
parser.add_argument(, =)
parser.add_argument(, =)
parser.add_argument(, choices=[, ], default=, =)
args = parser.parse_args()
scorer = DocumentQualityScorer(args.file)
:
result = scorer.score_document()
args. == :
args.output:
(args.output, , encoding=) f:
json.dump(result, f, indent=, ensure_ascii=)
()
:
(json.dumps(result, indent=, ensure_ascii=))
:
result:
()
exit()
( * )
()
( * )
()
()
()
()
()
metric result[]:
()
()
()
metric[]:
()
issue metric[]:
()
()
result[]:
()
i, rec (result[], ):
()
()
grade_descriptions = {
: ,
: ,
: ,
: ,
:
}
()
()
Exception e:
()
exit()