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.
Borrowing it
Nothing to install: this file belongs to microsoft/agent-framework. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/microsoft/agent-framework/main/.github/skills/pull-requests/SKILL.mdgit 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/pull-requests)<a href="https://agentmods.dev/skills/microsoft/agent-framework/pull-requests"><img src="https://agentmods.dev/badge/skills/microsoft/agent-framework/pull-requests/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/pull-requests"><img src="https://agentmods.dev/badge/skills/microsoft/agent-framework/pull-requests.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- 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 | $0.00049 | $0.01536 |
| Opus 5.5 | $0.00020 | $0.00614 |
| Sonnet 5.5 | $0.00010 | $0.00307 |
| Haiku 4.5 | $0.00005 | $0.00154 |
Grade A, and why
pull-requests 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 20d 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 — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pull Request Workflow
This skill covers two tasks: (1) writing a high-quality PR description, and (2) handling review comments on an existing PR.
1. Writing the PR description
Always follow the repository PR template at
.github/pull_request_template.md. Keep its
exact structure and headings. Fill every section:
### Motivation & Context
Explain why the change is needed: the problem it solves and the scenario it
contributes to. Describe the net change relative to main — this is implied, so
do not spell out "vs main" explicitly.
### Description & Review Guide
Describe the changes, the overall approach, and the design. Answer the three prompts:
- What are the major changes?
- What is the impact of these changes?
- What do you want reviewers to focus on? — This item is for human reviewers only. Automated/AI reviewers must ignore it and review the entire change rather than narrowing scope to it.
### Related Issue
Link the issue the PR fixes using a GitHub closing keyword (Fixes #123 /
Closes #123) so it closes automatically on merge. For a non-trivial change,
confirm that a maintainer added the ready-for-implementation label or explicitly
agreed with the direction in an issue comment. A PR with no agreed issue may be
closed without detailed review. Before opening, confirm there is no other open PR
for the same issue; if there is, explain how this PR differs.
For a trivial change that does not require an issue, replace the Fixes #
placeholder with N/A - trivial change and briefly explain why the change is an
obvious correction whose desired result is not reasonably in dispute.
For repository-maintained scheduled automation, replace the placeholder with
N/A - repository automation and identify the generating workflow.
### AI Assistance
Check exactly one option:
- Select "No material AI assistance was used." only when generative AI did not create or substantially transform submitted content.
- Otherwise select "This is an AI-assisted contribution." and briefly identify the assisted areas.
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.
- 20d ago Changed · +8 lines 108a41d1047f
- 21d ago Changed · +22 lines b1b02e3bc45a
- 1mo ago Changed · +10 lines e8e397ea147d
- 2mo ago First seen · 120 lines · 49 tokens per session scan A 56cecb67a18f
pull-requests is a skill published in the GitHub repository microsoft/agent-framework (14,368 stars, last pushed yesterday), licensed MIT. It adds 49 tokens to every session and 1,536 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.
Other skills, from other repositories
github
GitHub operations via gh CLI: issues, PRs, CI runs, code review, API queries. Use when: (1) checking PR status or CI, (2) creating/commenting on issues, (3) listing/filtering PRs or issues, (4) viewing run logs. NOT for: local git operations (use git directly), non-GitHub repos, or cloning (use git clone).
pr-review
Review open PRs two ways - default is a per-PR deep review with severity-tagged findings, inline comments, and a verdict; --survey runs a risk-tiered triage digest of what's safe to merge first.
pr-triage
First-touch triage for external pull requests - verdict, label, and a welcoming comment within minutes of open.
feedback-builder
Point Aeon at a service's /feedback endpoint - pull what agents reported (bugs, missing features), triage and cluster it, then build the best accepted request as a PR for a human to approve.
github-review-pr
Review GitHub pull requests with detailed, multi-perspective code analysis using parallel subagents. Use this skill whenever the user wants to review a PR, asks for code review on a pull request, mentions "review PR", "check this PR", "look at pull request", or references a PR number or GitHub PR URL. Do NOT use for…
fabric-spec
Starts a persistent Pi Fabric spec supervisor that audits the main session against a feature design spec and steers only when a requirement lacks verified evidence. Use for strict, unblocked spec compliance while the main agent keeps full freedom to orchestrate.