Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/dean0x/devflow/pythonnpx skills add dean0x/devflow --skill pythongit clone --depth 1 https://github.com/dean0x/devflowWhat it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00065 | $0.01195 |
| Opus 5 | $0.00032 | $0.00598 |
| Sonnet 5 | $0.00013 | $0.00239 |
| Haiku 4.5 | $0.00006 | $0.00120 |
Grade A, and why
python scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Patterns
Iron Law
EXPLICIT IS BETTER THAN IMPLICIT [3]
Type-hint every function signature. Name every exception. Use dataclasses over raw dicts. Python's flexibility is a strength only when boundaries are explicit.
When This Skill Activates
Working with Python codebases, designing typed APIs, modeling data with dataclasses or Pydantic, implementing async code, structuring Python packages.
Type Safety
Type Hint Everything [4][17][18]
# BAD: def process(data, config): ...
def process(data: list[dict[str, Any]], config: AppConfig) -> ProcessResult: ...
Dropbox's 4M-line mypy migration eliminated entire bug classes [18]. Use
from __future__ import annotations for forward references [22].
Protocols for Structural Typing [5][1]
from typing import Protocol
class Repository(Protocol):
def find_by_id(self, id: str) -> User | None: ...
def save(self, entity: User) -> User: ...
PEP 544 formalizes duck typing as "static duck typing" — no implements
required [5]. Any class with matching methods satisfies the Protocol [1].
Strict Optional Handling [4][23]
PEP 604 X | Y syntax replaces verbose Optional[X] [23]:
def get_name(user: User | None) -> str:
return "Anonymous" if user is None else user.name
Error Handling [2][8][9]
class AppError(Exception): ...
class NotFoundError(AppError):
def __init__(self, entity: str, id: str) -> None:
super().__init__(f"{entity} {id} not found")
self.entity, self.id = entity, id
@contextmanager
def database_transaction(conn: Connection):
try:
yield conn; conn.commit()
except Exception:
conn.rollback(); raise
Google Style Guide prohibits bare except: — catches SystemExit [8].
Cosmic Python wraps the unit-of-work in a context manager [9].
Data Modeling [6][12][14]
# Internal value objects — frozen enforces immutability [6][14]
@dataclass(frozen=True)
class User:
name: str
email: str
created_at: datetime = field(default_factory=lambda: datetime.now(timezone.utc))
# API boundary models — Pydantic validates on instantiation [12]
class CreateUserRequest(BaseModel):
name: str
email: EmailStr
age: int = Field(ge=0, le=150)
What ships with it
5 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- yesterday First seen · 157 lines · 65 tokens per session scan A 2d792e5ea867
python is a skill published in the GitHub repository dean0x/devflow (19 stars, last pushed yesterday), licensed MIT. It adds 65 tokens to every session and 1,195 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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安全校验关卡。自动扫描代码安全漏洞,检测危险模式,确保安全决策有文档记录。当用户提到安全扫描、漏洞检测、安全审计、代码安全、OWASP、注入检测、敏感信息泄露时使用。在新建模块、安全相关变更、攻防任务、重构完成时自动触发。.
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verify-module
模块完整性校验关卡。扫描目录结构、检测缺失文档、验证代码与文档同步。当用户提到模块校验、文档检查、结构完整性、README检查、DESIGN检查时使用。在新建模块完成时自动触发。.