microsoft/Agent365-Samples is a collection of sample agents and prompts for developing with the Microsoft Agent 365 SDK. It is for developers building agents for Microsoft 365, Teams, Copilot Studio, Webchat, and related development environments in several programming languages. The catalogue entries are examples and instructions built around these samples.
Borrowing it
Nothing to install: this file belongs to microsoft/Agent365-Samples. 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/Agent365-Samples/main/.claude/commands/review-pr.mdgit clone --depth 1 https://github.com/microsoft/Agent365-SamplesWrote 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/commands/microsoft/agent365-samples/review-pr)<a href="https://agentmods.dev/commands/microsoft/agent365-samples/review-pr"><img src="https://agentmods.dev/badge/commands/microsoft/agent365-samples/review-pr/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/commands/microsoft/agent365-samples/review-pr"><img src="https://agentmods.dev/badge/commands/microsoft/agent365-samples/review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.01912 |
| Opus 5.5 | $0.00000 | $0.00765 |
| Sonnet 5.5 | $0.00000 | $0.00382 |
| Haiku 4.5 | $0.00000 | $0.00191 |
Grade A, and why
review-pr scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 219 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review Pull Request
Review code changes in a specific pull request using a comprehensive multi-agent code review process with specialized reviewers for security, patterns, quality, and standards.
Usage
/review-pr <PR_NUMBER>
Examples:
/review-pr 123- Review pull request #123/review-pr 45- Review pull request #45
Instructions
You are coordinating a comprehensive code review for pull request #$ARGUMENTS.
Step 1: Gather PR Information
First, collect information about the pull request:
-
Get PR details, changed files, and the HEAD commit SHA:
gh pr view $ARGUMENTS --json number,title,body,baseRefName,headRefName,headRefOid,url,files gh pr diff $ARGUMENTS -
Extract key information:
- List of changed files
- PR URL for linking in review comments
- HEAD commit SHA (
headRefOid) - required for posting inline comments
-
IMPORTANT: Save the diff output - you will need it to:
- Include relevant diff context snippets in each finding
- Determine the exact diff line numbers for inline comments (line numbers as they appear in the diff, not file line numbers)
- Determine the side (RIGHT for additions
+, LEFT for deletions-)
-
Create the
.codereviews/directory if it doesn't exist.
Step 2: Launch Parallel Code Reviews
Launch FOUR sub-agents in parallel using the Task tool. Each agent MUST receive:
- The PR number: $ARGUMENTS
- The list of changed files (so they stay scoped to PR files only)
- The PR URL for generating clickable links
CRITICAL: You MUST launch all four agents in a SINGLE message with FOUR parallel Task tool calls:
- security-compliance-reviewer (
subagent_type: security-compliance-reviewer)- Prompt: "Review PR #$ARGUMENTS for security compliance. Files changed: [list files]. PR URL: [url]. Focus on authentication, secrets, token handling, logging security, and input validation. Output your review in the structured markdown format."
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.
- 1mo ago First seen · 219 lines · 0 tokens per session scan A e879cfe4dfa8
review-pr is a command published in the GitHub repository microsoft/Agent365-Samples (112 stars, last pushed yesterday), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,912 tokens. 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 commands, from other repositories
refactor
Systematic code refactoring with smart scope detection.
review-branch
Review the current branch's diff against base by dispatching atomic-reviewer. No orchestration loop, no spec required — pre-flight before /commit pr or /commit merge.
init
Install the formatters this repository needs, with every command visible before it runs.
merge-conflict-analysis
You are analyzing merge conflicts for PR #${{ pr-number }}.
boot
Start a new PromptKit prompt assembly session (alias for /bootstrap).
repo-audit
Audit a codebase (local or remote GitHub/GitLab) against architecture principles and requirements, surfacing drift, risk, and missing decisions.