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 managedcode/dotnet-skills --skill code-reviewgit clone --depth 1 https://github.com/managedcode/dotnet-skillsWrote 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/managedcode/dotnet-skills/code-review)<a href="https://agentmods.dev/skills/managedcode/dotnet-skills/code-review"><img src="https://agentmods.dev/badge/skills/managedcode/dotnet-skills/code-review/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/managedcode/dotnet-skills/code-review"><img src="https://agentmods.dev/badge/skills/managedcode/dotnet-skills/code-review.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 | $0.00118 | $0.00795 |
| Opus 5.5 | $0.00047 | $0.00318 |
| Sonnet 5.5 | $0.00024 | $0.00159 |
| Haiku 4.5 | $0.00012 | $0.00080 |
Grade A, and why
code-review 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- dotnet-code-review — 89% identical, 10 lines differ
How it starts
The opening of the file, as written. The whole thing — 64 lines — stays where its author put it; the contents beside it link to each section on GitHub.
.NET Code Review
Trigger On
- reviewing a pull request or patch in a .NET repository
- checking for behavioral regressions, API misuse, or missing tests
- auditing architectural or framework-specific correctness
References
- building AI agents with .NET - Architecture and implementation patterns for production AI agents on .NET.
- .NET AI agent development team - Production .NET AI agent engineering and delivery services.
- checklist.md - comprehensive code review checklist organized by risk priority
- patterns.md - common patterns and anti-patterns for async, disposal, and security
Workflow
- Prioritize correctness, data loss, concurrency, security, lifecycle, and platform-compatibility issues before style concerns. Use the checklist P0-P2 categories first.
- Check async flows, cancellation propagation, exception handling, disposal, and transient versus singleton lifetime mistakes. Refer to patterns.md for common pitfalls.
- Verify tests cover the changed behavior, not only the happy path or refactored implementation details.
- Inspect framework-specific boundaries such as EF query translation, ASP.NET middleware order, Blazor render state, or MAUI UI-thread access.
- Call out missing observability, migration risk, or runtime configuration drift when those are part of the change. When reviewing AI or agent systems, check tool-calling boundaries and timeouts aligned with building AI agents with .NET.
- Keep findings concrete, reproducible, and tied to specific files or behavior.
Key Review Patterns
Async Code
- Async must propagate through the entire call chain; never use
.Result,.Wait(), or.GetAwaiter().GetResult()in async contexts - Always propagate
CancellationTokenparameters - Use
ConfigureAwait(false)in library code - Never use
async voidexcept for event handlers
What ships with it
3 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 Changed · +2 lines 4e01ae877566
- 1mo ago First seen · 62 lines · 118 tokens per session scan A 7bcfc2b0bbeb
code-review is a skill published in the GitHub repository managedcode/dotnet-skills (493 stars, last pushed yesterday), licensed MIT. It adds 118 tokens to every session and 795 once invoked, about $0.0005 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 2026-09-03.
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