chore(skills): добавлены скиллы docstring и security-audit

- Зачем:
  - напоминание моделям про Google-style docstring'ы и Ruff-конфиг.
  - чеклист безопасности для ревью кода и зависимостей.
- Что:
  - добавлен docstring (DeerHide): вычищены мёртвые ссылки, добавлен Ruff select, правило языка проекта.
  - добавлен security-audit: чеклист OWASP, severity-уровни, формат отчёта.
  - убраны test-generator (Node.js стек) и api-docs (избыточен).
- Проверка:
  - ls agents/.agents/skills/{docstring,security-audit}/SKILL.md.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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---
name: python-docstring
description: A skill for writing consistent, well-structured Python docstrings following the Google style convention.
metadata:
author: Deerhide
version: 1.0.0
---
# Python Docstring Skill
## When to use this skill?
- Use this skill when writing or updating Python documentation strings (docstrings).
- This skill is useful for ensuring consistent documentation across a Python codebase.
- It should be applied when documenting modules, classes, functions, methods, and attributes.
- Use it during code reviews to verify docstring quality and completeness.
# Language
Язык docstring'ов определяется по проекту: если в существующем коде комментарии и docstring'ы на русском — пиши на русском, если на английском — на английском. Не смешивай языки внутри одного проекта.
# Docstring Style Convention
We follow the **Google style** docstring convention. This style is chosen for its:
- Readability and clean formatting
- Wide adoption in the Python community
- Excellent support in documentation tools (Sphinx, MkDocs)
- Native support in linting tools (Ruff, Pylint)
# Module Docstrings
Every Python module should start with a docstring describing its purpose.
```python
"""Module for handling user authentication and session management.
This module provides utilities for user authentication, token generation,
and session lifecycle management. It integrates with OAuth2 providers
and supports JWT-based authentication.
Example:
Basic usage of the authentication service::
from auth import AuthService
service = AuthService(secret_key="my-secret")
token = service.create_token(user_id=123)
Attributes:
DEFAULT_TOKEN_EXPIRY (int): Default token expiration time in seconds.
SUPPORTED_ALGORITHMS (list): List of supported JWT algorithms.
Todo:
* Add support for refresh tokens
* Implement rate limiting for failed attempts
"""
DEFAULT_TOKEN_EXPIRY = 3600
SUPPORTED_ALGORITHMS = ["HS256", "RS256"]
```
# Class Docstrings
Class docstrings should describe the class purpose and list its attributes.
```python
class UserRepository:
"""Repository for managing user data persistence.
This class provides CRUD operations for user entities and handles
database connections and transactions.
Attributes:
connection: Database connection instance.
table_name: Name of the users table.
cache_enabled: Whether caching is enabled for queries.
Example:
Creating and using a repository::
repo = UserRepository(connection=db_conn)
user = repo.find_by_id(user_id=42)
repo.save(user)
"""
def __init__(self, connection: DatabaseConnection) -> None:
"""Initialize the UserRepository.
Args:
connection: Active database connection to use for operations.
"""
self.connection = connection
self.table_name = "users"
self.cache_enabled = True
```
# Function and Method Docstrings
Functions and methods should document their purpose, arguments, return values, and exceptions.
## Basic Function
```python
def calculate_discount(price: float, percentage: float) -> float:
"""Calculate the discounted price.
Args:
price: Original price of the item.
percentage: Discount percentage (0-100).
Returns:
The discounted price after applying the percentage reduction.
Raises:
ValueError: If percentage is not between 0 and 100.
TypeError: If price or percentage are not numeric.
Example:
>>> calculate_discount(100.0, 20)
80.0
"""
if not 0 <= percentage <= 100:
raise ValueError("Percentage must be between 0 and 100")
return price * (1 - percentage / 100)
```
## Method with Complex Arguments
```python
def create_user(
self,
username: str,
email: str,
*,
role: str = "user",
metadata: dict[str, Any] | None = None,
) -> User:
"""Create a new user in the system.
Creates a user entity with the provided information and persists
it to the database. Sends a welcome email upon successful creation.
Args:
username: Unique username for the new user. Must be alphanumeric
and between 3-50 characters.
email: Valid email address for the user.
role: User role assignment. Defaults to "user".
Valid options are "user", "admin", "moderator".
metadata: Optional dictionary of additional user metadata.
Keys must be strings, values can be any JSON-serializable type.
Returns:
The newly created User instance with assigned ID.
Raises:
DuplicateUserError: If username or email already exists.
ValidationError: If input validation fails.
DatabaseError: If database operation fails.
Note:
This method triggers a background task for sending the welcome email.
The email sending is non-blocking and failures are logged but not raised.
Example:
Creating a basic user::
user = service.create_user(
username="johndoe",
email="john@example.com"
)
Creating an admin user with metadata::
admin = service.create_user(
username="admin",
email="admin@example.com",
role="admin",
metadata={"department": "IT"}
)
"""
```
## Async Functions
```python
async def fetch_user_data(user_id: int, timeout: float = 30.0) -> UserData:
"""Fetch user data from the remote service.
Asynchronously retrieves user information from the external API
with automatic retry logic for transient failures.
Args:
user_id: Unique identifier of the user to fetch.
timeout: Maximum time in seconds to wait for response.
Defaults to 30.0 seconds.
Returns:
UserData object containing the user's information.
Raises:
UserNotFoundError: If no user exists with the given ID.
TimeoutError: If the request exceeds the timeout duration.
ServiceUnavailableError: If the remote service is unreachable.
"""
```
# Generator and Iterator Docstrings
```python
def paginate_results(
query: Query,
page_size: int = 100,
) -> Iterator[list[Record]]:
"""Paginate through query results.
Yields pages of records from the query, handling cursor-based
pagination automatically.
Args:
query: Database query to paginate.
page_size: Number of records per page. Defaults to 100.
Yields:
Lists of Record objects, each list containing up to page_size items.
Example:
>>> for page in paginate_results(query, page_size=50):
... process_records(page)
"""
```
# Property Docstrings
```python
@property
def full_name(self) -> str:
"""Return the full name of the user.
Combines first_name and last_name with proper spacing.
Returns an empty string if both names are unset.
"""
return f"{self.first_name} {self.last_name}".strip()
@property
def is_active(self) -> bool:
"""Return whether the user account is currently active.
An account is considered active if it has been verified
and has not been suspended or deleted.
"""
return self.verified and not self.suspended
```
# Context Manager Docstrings
```python
@contextmanager
def database_transaction(
connection: Connection,
isolation_level: str = "READ_COMMITTED",
) -> Iterator[Transaction]:
"""Context manager for database transactions.
Provides automatic commit on success and rollback on failure.
Nested transactions are supported via savepoints.
Args:
connection: Active database connection.
isolation_level: Transaction isolation level.
Options: "READ_UNCOMMITTED", "READ_COMMITTED",
"REPEATABLE_READ", "SERIALIZABLE".
Defaults to "READ_COMMITTED".
Yields:
Transaction object for executing queries.
Raises:
TransactionError: If transaction cannot be started.
Example:
>>> with database_transaction(conn) as tx:
... tx.execute("INSERT INTO users VALUES (?)", [user])
"""
```
# Dataclass and Pydantic Model Docstrings
```python
@dataclass
class OrderItem:
"""Represents a single item in an order.
Attributes:
product_id: Unique identifier of the product.
quantity: Number of units ordered. Must be positive.
unit_price: Price per unit in the order currency.
discount: Applied discount as a decimal (0.0-1.0).
"""
product_id: str
quantity: int
unit_price: Decimal
discount: Decimal = Decimal("0.0")
class UserSettings(BaseModel):
"""User preference settings.
Stores user-configurable settings for the application,
including notification preferences and display options.
Attributes:
theme: UI theme preference. Either "light" or "dark".
notifications_enabled: Whether to send notifications.
language: Preferred language code (ISO 639-1).
timezone: User's timezone (IANA format).
"""
theme: Literal["light", "dark"] = "light"
notifications_enabled: bool = True
language: str = "en"
timezone: str = "UTC"
```
# Enum Docstrings
```python
class OrderStatus(Enum):
"""Status values for order lifecycle.
Attributes:
PENDING: Order created but not yet processed.
CONFIRMED: Order confirmed and awaiting fulfillment.
SHIPPED: Order has been shipped to customer.
DELIVERED: Order successfully delivered.
CANCELLED: Order was cancelled before fulfillment.
"""
PENDING = "pending"
CONFIRMED = "confirmed"
SHIPPED = "shipped"
DELIVERED = "delivered"
CANCELLED = "cancelled"
```
# Exception Docstrings
```python
class ValidationError(Exception):
"""Raised when input validation fails.
This exception is raised when user input or API request data
fails validation rules.
Attributes:
field: Name of the field that failed validation.
message: Human-readable error message.
code: Machine-readable error code for client handling.
Example:
>>> raise ValidationError(
... field="email",
... message="Invalid email format",
... code="INVALID_EMAIL"
... )
"""
def __init__(self, field: str, message: str, code: str) -> None:
"""Initialize ValidationError.
Args:
field: Name of the field that failed validation.
message: Human-readable description of the error.
code: Machine-readable error code.
"""
self.field = field
self.message = message
self.code = code
super().__init__(f"{field}: {message}")
```
# Docstring Sections Reference
The following sections are supported in Google style docstrings:
| Section | Purpose |
|---------|---------|
| `Args:` | Document function/method parameters |
| `Returns:` | Describe the return value |
| `Yields:` | Describe yielded values (generators) |
| `Raises:` | List exceptions that may be raised |
| `Attributes:` | Document class/module attributes |
| `Example:` / `Examples:` | Provide usage examples |
| `Note:` | Additional information or caveats |
| `Warning:` | Important warnings for users |
| `Todo:` | Future improvements or tasks |
| `See Also:` | References to related functions/classes |
# Best Practices
1. **Be Concise**: First line should be a brief summary under 79 characters.
2. **Use Imperative Mood**: Write "Calculate the sum" not "Calculates the sum".
3. **Document All Public APIs**: Every public function, class, and method needs a docstring.
4. **Rely on Type Hints**: Avoid duplicating type information in docstrings when type hints are present. Modern documentation tools extract types from annotations.
5. **Provide Examples**: Complex functions benefit from usage examples.
6. **Document Exceptions**: List all exceptions that can be raised.
7. **Keep Updated**: Update docstrings when code changes.
8. **Use Proper Indentation**: Continuation lines should be indented consistently.
# Linting Configuration
Recommended Ruff configuration for `pyproject.toml`:
```toml
[tool.ruff]
line-length = 120
[tool.ruff.lint]
select = ["D", "F", "E", "W", "I", "UP", "B", "SIM", "S", "A", "C90", "RET", "PERF"]
[tool.ruff.lint.pydocstyle]
convention = "google"
```
Key rule groups: **D** (docstrings), **F** (pyflakes), **E/W** (pycodestyle),
**I** (imports), **UP** (pyupgrade), **B** (bugbear), **SIM** (simplify),
**S** (security/bandit), **A** (builtins shadowing), **C90** (complexity),
**RET** (return statements), **PERF** (performance).
# Common Ruff Docstring Rules
| Rule | Description |
|------|-------------|
| D100 | Missing docstring in public module |
| D101 | Missing docstring in public class |
| D102 | Missing docstring in public method |
| D103 | Missing docstring in public function |
| D107 | Missing docstring in `__init__` |
| D200 | One-line docstring should fit on one line |
| D205 | 1 blank line required between summary and description |
| D400 | First line should end with a period |
| D401 | First line should be in imperative mood |
| D417 | Missing argument descriptions in docstring |
@@ -0,0 +1,228 @@
---
name: security-audit
description: Audit code and dependencies for security vulnerabilities. Use when reviewing PRs, checking dependencies, preparing for deployment, or when user mentions security, vulnerabilities, or audit.
---
# Security Audit Skill
Perform comprehensive security audits on codebases to identify vulnerabilities before they reach production.
## When to Use This Skill
- User mentions "security", "audit", "vulnerability", "CVE"
- Before deployment commands
- During PR reviews
- User asks about dependencies
- Periodic security checks
## Audit Checklist
### 1. Secrets Exposure
**Check for hardcoded secrets:**
```bash
# Search for common secret patterns
grep -rn "API_KEY\|SECRET\|TOKEN\|PASSWORD" --include="*.{js,ts,py,go,rb,java}" .
grep -rn "sk-\|pk_\|api_\|secret_" --include="*.{js,ts,py,go,rb,java}" .
```
**Verify .gitignore:**
```bash
# Ensure sensitive files are ignored
cat .gitignore | grep -E "\.env|secret|credential|\.pem|\.key"
```
**Check git history for leaked secrets:**
```bash
# Search recent commits (requires git-secrets or truffleHog)
git log -p --all -S "API_KEY" --since="30 days ago"
```
✅ Pass criteria:
- No hardcoded API keys, tokens, or passwords
- `.env` files in `.gitignore`
- No secrets in git history
### 2. Dependency Vulnerabilities
**Node.js:**
```bash
npm audit
# or
yarn audit
# or
pnpm audit
```
**Python:**
```bash
pip-audit
# or
safety check
```
**Go:**
```bash
govulncheck ./...
```
**Rust:**
```bash
cargo audit
```
✅ Pass criteria:
- No critical vulnerabilities
- No high vulnerabilities > 30 days old
- Dependencies updated within last 90 days
### 3. Input Validation
**Check for:**
- User inputs sanitized before use
- SQL queries use parameterized statements
- File paths validated and sandboxed
- HTML content escaped before rendering
- Command injection prevention
**Common vulnerable patterns:**
```javascript
// BAD: SQL injection
db.query(`SELECT * FROM users WHERE id = ${userId}`)
// GOOD: Parameterized query
db.query('SELECT * FROM users WHERE id = ?', [userId])
```
```python
# BAD: Command injection
os.system(f"convert {user_file}")
# GOOD: Use subprocess with list
subprocess.run(["convert", user_file], check=True)
```
### 4. Authentication & Authorization
**Check for:**
- Passwords hashed with bcrypt/argon2 (not MD5/SHA1)
- Session tokens are cryptographically random
- Sessions expire appropriately
- CSRF protection on state-changing endpoints
- Rate limiting on auth endpoints
- Account lockout after failed attempts
**Look for:**
```javascript
// BAD: Weak hashing
crypto.createHash('md5').update(password)
// GOOD: Bcrypt
bcrypt.hash(password, 12)
```
### 5. HTTPS & Transport Security
**Check for:**
- HTTPS enforced (HSTS header)
- Secure cookie flags (`Secure`, `HttpOnly`, `SameSite`)
- No mixed content warnings
- TLS 1.2+ required
### 6. Error Handling
**Check for:**
- Stack traces not exposed in production
- Generic error messages for users
- Detailed errors only in logs
- Sensitive data not in error messages
```javascript
// BAD: Exposes internals
res.status(500).send({ error: err.stack })
// GOOD: Generic message
res.status(500).send({ error: 'An unexpected error occurred' })
```
### 7. File Upload Security
If file uploads exist:
- Validate file type server-side (not just extension)
- Limit file size
- Scan for malware
- Store outside webroot
- Rename uploaded files
### 8. API Security
- Authentication required on all sensitive endpoints
- Authorization checks per resource
- Rate limiting implemented
- CORS configured restrictively
- API versioning in place
## Severity Levels
| Level | Description | Action Required |
|-------|-------------|-----------------|
| 🔴 Critical | Actively exploitable | Block deployment |
| 🟠 High | Exploitable with effort | Fix within 7 days |
| 🟡 Medium | Requires conditions | Fix within 30 days |
| 🟢 Low | Minimal impact | Fix when convenient |
## Output Format
```markdown
## Security Audit Results
**Project:** [name]
**Date:** [date]
**Auditor:** Claude (automated)
### Summary
| Severity | Count |
|----------|-------|
| 🔴 Critical | 0 |
| 🟠 High | 1 |
| 🟡 Medium | 2 |
| 🟢 Low | 3 |
### Findings
#### 1. [🟠 High] Hardcoded API Key
**Location:** `src/config.js:15`
**Description:** API key for payment provider is hardcoded
**Risk:** If source code is leaked, attackers gain API access
**Recommendation:** Move to environment variable
```diff
- const STRIPE_KEY = 'sk_live_abc123...'
+ const STRIPE_KEY = process.env.STRIPE_SECRET_KEY
```
#### 2. [🟡 Medium] Missing Rate Limiting
**Location:** `src/routes/auth.js`
**Description:** Login endpoint has no rate limiting
**Risk:** Enables brute force attacks
**Recommendation:** Add rate limiting middleware
### Recommendations
1. [ ] Fix critical and high issues before next deployment
2. [ ] Schedule medium issues for next sprint
3. [ ] Add low issues to backlog
4. [ ] Re-run audit after fixes
```
## Commands to Run
After completing the audit, provide the user with:
1. Summary of findings
2. Prioritized fix list
3. Commands to address each issue
4. Timeline recommendation