Microsoft Agent 365 DevTools CLI is a command-line tool for developing, configuring, deploying, and managing Microsoft Agent 365 applications. Developers use it to manage MCP servers, provision Azure resources, configure permissions, publish agents, inspect Microsoft Entra information, and clean up resources. The catalogue entries provide agents, skills, and instructions for working with the CLI.
Borrowing it
Nothing to install: this file belongs to microsoft/Agent365-devTools. 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-devTools/main/.claude/skills/review-pr/SKILL.mdgit clone --depth 1 https://github.com/microsoft/Agent365-devToolsWrote 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/agent365-devtools/review-pr)<a href="https://agentmods.dev/skills/microsoft/agent365-devtools/review-pr"><img src="https://agentmods.dev/badge/skills/microsoft/agent365-devtools/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/skills/microsoft/agent365-devtools/review-pr"><img src="https://agentmods.dev/badge/skills/microsoft/agent365-devtools/review-pr.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- 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 | $0.00031 | $0.01709 |
| Opus 5.5 | $0.00012 | $0.00684 |
| Sonnet 5.5 | $0.00006 | $0.00342 |
| Haiku 4.5 | $0.00003 | $0.00171 |
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 — 153 lines — stays where its author put it; the contents beside it link to each section on GitHub.
PR Review Skill
Generate and post AI-powered PR review comments to GitHub following engineering best practices.
Usage
/review-pr <pr-number> # Generate review (step 1)
/review-pr <pr-number> --post # Post review to GitHub (step 2)
Examples:
/review-pr 180- Generate review and save to YAML file/review-pr 180 --post- Post the reviewed YAML to GitHub
What this skill does
Step 1: Generate (/review-pr <number>)
- Fetches PR details from GitHub using the gh CLI
- Performs architectural review (NEW!): Questions design decisions, checks for scope creep, validates use cases
- Analyzes changes for security, testing, design patterns, and code quality issues
- Differentiates contexts: CLI code vs GitHub Actions code (different standards)
- Creates actionable feedback: Specific refactoring suggestions based on file names and patterns
- Generates structured review comments in an editable YAML file
- Shows preview of all generated comments
Step 2: Post (/review-pr <number> --post)
- Reads the YAML file you reviewed/edited
- Posts to GitHub: Submits all enabled comments to the PR
- Automatic fallback: If GitHub API posting fails (e.g., Enterprise Managed User restrictions), automatically generates a markdown file with formatted comments for manual copy/paste
Engineering Review Principles
This skill enforces the following principles:
Architectural Review (NEW!)
- Design Decision Validation: Questions "why" before reviewing "how"
- Scope Creep Detection: Flags expansions beyond Agent365 deployment/management
- Use Case Validation: Requires concrete scenarios for new features
- Overlap Detection: Identifies duplication with existing tools (Azure CLI, Portal)
- YAGNI Enforcement: Questions features without documented need
Architecture & Patterns
- .NET architect patterns: Reviews follow .NET best practices
- Azure CLI alignment: Ensures consistency with az cli patterns and conventions
- Cross-platform compatibility: Validates Windows, Linux, and macOS compatibility (for CLI code)
What ships with it
2 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.
- 1mo ago First seen · 153 lines · 31 tokens per session scan A 84e9de25509c
review-pr is a skill published in the GitHub repository microsoft/Agent365-devTools (61 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 1,709 once invoked, about $0.0001 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
review-implement-phase
Implements triaged review actions, commits focused fixes, and posts Done plus resolves threads. Use when the user wants only the implementation phase of the review-framework workflow.
pr
Draft a PR body from OMC's paper trail — the smallest visual that proves the change, evidence consumed from the verify protocol (never re-collected), reversibility from the ADR test on the diff, glossary language throughout.
otto-pr-review-loop
Run Polly and OCR on a PR until all findings settle.
engram-branch-pr
PR creation workflow for Engram following the issue-first enforcement system. Trigger: When creating a pull request, opening a PR, or preparing changes for review.
verify-behavior
Verify or reproduce visible product behavior by driving the real UI with pi-computer-use's checked tools, requiring verified expect postconditions and durable state evidence for meaningful UI flows. Use when triage needs visual reproduction, implementation needs behavioral proof, review needs interactive confirmation…
github-contributor
A step-by-step guide for contributing code, tests, documentation, or build changes to open-source projects you do not maintain. It explains how to prepare a pull request that follows the project’s rules and is easier for maintainers to review.