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/microsoft/agent-framework/python-developmentnpx skills add microsoft/agent-framework --skill python-developmentgit clone --depth 1 https://github.com/microsoft/agent-frameworkWhat 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 | $0.00035 | $0.01099 |
| Opus 5 | $0.00017 | $0.00549 |
| Sonnet 5 | $0.00007 | $0.00220 |
| Haiku 4.5 | $0.00003 | $0.00110 |
Grade A, and why
python-development 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 — 128 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Development Standards
File Header
Every .py file must start with:
# Copyright (c) Microsoft. All rights reserved.
Type Annotations
- Always specify return types and parameter types
- Use
Type | Noneinstead ofOptional[Type] - Use
from __future__ import annotationsto enable postponed evaluation - Use suffix
Tfor TypeVar names:ChatResponseT = TypeVar("ChatResponseT", bound=ChatResponse) - Use
Mappinginstead ofMutableMappingfor read-only input parameters - Prefer
# type: ignore[...]over unnecessary casts, orisinstancechecks, when these are internally called and executed methods But make sure the ignore is specific for both mypy and pyright so that we don't miss other mistakes - Internal private helpers may be used across
agent_framework*modules when intentional; use a targeted# pyright: ignore[reportPrivateUsage]instead of making the helper public just to satisfy pyright. - Do not add trivial pass-through or one-line helper functions solely to appease typing. Prefer targeted ignores, casts, or clearer annotations over adding runtime overhead without a design benefit.
Function Parameters
- Positional parameters: up to 3 fully expected parameters
- Use keyword-only arguments (after
*) for optional parameters - Provide string-based overrides to avoid requiring extra imports:
def create_agent(name: str, tool_mode: Literal['auto', 'required', 'none'] | ChatToolMode) -> Agent:
if isinstance(tool_mode, str):
tool_mode = ChatToolMode(tool_mode)
- Avoid shadowing built-ins (use
next_handlerinstead ofnext) - Avoid
**kwargsunless needed for subclass extensibility; prefer named parameters
Docstrings
Use Google-style docstrings for all public APIs:
def equal(arg1: str, arg2: str) -> bool:
"""Compares two strings and returns True if they are the same.
Args:
arg1: The first string to compare.
arg2: The second string to compare.
Returns:
True if the strings are the same, False otherwise.
Raises:
ValueError: If one of the strings is empty.
"""
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 · 128 lines · 35 tokens per session scan A e47f1df06e46
python-development is a skill published in the GitHub repository microsoft/agent-framework (13,222 stars, last pushed 2d ago), licensed MIT. It adds 35 tokens to every session and 1,099 once invoked, about $0.0002 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.
Other skills, from other repositories
swarmclaw
AI agent runtime and multi-agent orchestration platform. Teaches agents how to use SwarmClaw's 6 primitive tools, persistent memory, dreaming, delegation, connectors, credentials, and the skill system. Use when an agent is running on SwarmClaw and needs to understand the platform's capabilities.
agent-collaboration
Use this skill when coordinating multiple AI agents. Covers multi-agent patterns, handoffs, and orchestration strategies.
crewai-multi-agent
Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies…
strands-review
Local preview of the strands-agents/devtools /strands review agent. Body is the upstream Task Reviewer SOP verbatim — do not paraphrase. Use when the user types /strands-review, asks for a "strands review" of a PR, or wants to anticipate what the remote /strands review GitHub Action will flag. Findings are close but…
docs-writer
Draft or rewrite Strands Agents documentation pages. Use when writing new doc pages, rewriting pages that failed audit, drafting sections for existing pages, or writing blog posts and release notes about Strands. Also triggers on "write a doc", "draft a page", "rewrite the quickstart", "add a tutorial for X"…
pr-writer
Generates pull request titles and descriptions. Use when the user asks to create, open, write, draft, or generate a PR, pull request, or merge request description.