Microsoft Agent Framework is a multi-language framework for building, coordinating, and running AI agents and workflows in Python and .NET. Teams use it for agent systems that need orchestration, collaboration, durability, observability, governance, or human involvement beyond a single prompt or chat loop. Catalogue add-ons provide skills and instructions for working with the framework.
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 skills add microsoft/agent-framework --skill python-package-managementgit clone --depth 1 https://github.com/microsoft/agent-frameworkWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/microsoft/agent-framework/python-package-management)<a href="https://agentmods.dev/skills/microsoft/agent-framework/python-package-management"><img src="https://agentmods.dev/badge/skills/microsoft/agent-framework/python-package-management/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/microsoft/agent-framework/python-package-management"><img src="https://agentmods.dev/badge/skills/microsoft/agent-framework/python-package-management.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk pass
- NVIDIA SkillSpector pass
What 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 5.1 | $0.00043 | $0.04689 |
| Opus 5.5 | $0.00017 | $0.01876 |
| Sonnet 5.5 | $0.00009 | $0.00938 |
| Haiku 4.5 | $0.00004 | $0.00469 |
Grade A, and why
python-package-management 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 2d ago.
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 — 385 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Python Package Management
Monorepo Structure
python/
├── pyproject.toml # Root package (agent-framework)
├── packages/
│ ├── core/ # agent-framework-core (main package)
│ ├── foundry/ # agent-framework-foundry
│ ├── lab/ # Standalone uv project, excluded from the root workspace
│ ├── anthropic/ # agent-framework-anthropic
│ └── ... # Other connector packages
agent-framework-corecontains core abstractions and OpenAI/Azure OpenAI built-in- Provider packages extend core with specific integrations
- Root
agent-frameworkdepends onagent-framework-core[all]. Despite the existing extra name, this is a curated standard install set, not every package at a particular lifecycle stage. - Entries in
agent-framework-core[all]carry lower and upper bounds. Workspace integrations use the version released with the current Core cohort as their lower bound so pip does not backtrack across old cycliccore[all] -> integration -> corecombinations. packages/labis intentionally excluded from the root uv workspace. It has its ownpyproject.toml,uv.lock, environment, CI matrix, and dependency updates so experimental dependencies cannot constrain released provider packages. Lab resolves released Core and provider distributions rather than local root-workspace packages.
Dependency Management
Uses uv for dependency management and poethepoet for task automation.
# Full setup (venv + install + prek hooks)
uv run poe setup
# Install dependencies from lockfile (frozen resolution with prerelease policy)
uv run poe install
# Create venv with specific Python version
uv run poe venv --python 3.12
# Intentionally upgrade a specific dependency to reduce lockfile conflicts
uv lock --upgrade-package <dependency-name> && uv run poe install
# Refresh exact development and on-demand tool pins, lockfiles, and validation
uv run poe upgrade-dev-dependencies
# Release cuts: refresh uv.lock and probe changed packages at both bound extremes.
# The release probe has a shared five-minute deadline.
uv run poe validate-python-release --base-ref upstream/main
# Exhaustive test+typing matrix (slow; use for deliberate dependency-range work or CI)
uv run poe validate-dependency-bounds-test
# Defaults to --package "*"; scope locally whenever possible.
uv run poe validate-dependency-bounds-test --package core
# Then expand bounds for one dependency in the target package
uv run poe validate-dependency-bounds-project --mode both --package core --dependency "<dependency-name>"
# Repo-wide automation can reuse the same task
uv run poe validate-dependency-bounds-project --mode upper --package "*"
# Add a dependency to one project and run both validators for that project/dependency
uv run poe add-dependency-and-validate-bounds --package core --dependency "<dependency-spec>"
# Work on the standalone Lab project
cd packages/lab
uv sync --all-extras --all-groups
uv run poe test
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.
- 2d ago Changed · +68 lines d99ee8eff479
- 3d ago Changed · +10 lines a25e44c72db5
- 13d ago Changed · +28 lines 425ff1430acf
- 1mo ago Changed · +13 lines b390ae540cc1
- 1mo ago First seen · 266 lines · 43 tokens per session scan A 016c91212e5a
python-package-management is a skill published in the GitHub repository microsoft/agent-framework (14,148 stars, last pushed today), licensed MIT. It adds 43 tokens to every session and 4,689 once invoked, about $0.0002 per session on Opus 5.5. 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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