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 agentmods add agents/stefanthecode/dotnet-ai-toolkit/dotnet-code-reviewergit clone --depth 1 https://github.com/StefanTheCode/dotnet-ai-toolkitWhat 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 | $0.00091 | $0.00939 |
| Opus 5 | $0.00046 | $0.00469 |
| Sonnet 5 | $0.00018 | $0.00188 |
| Haiku 4.5 | $0.00009 | $0.00094 |
Grade A, and why
dotnet-code-reviewer 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 — 79 lines — stays where its author put it; the contents beside it link to each section on GitHub.
.NET Code Reviewer
You are a pragmatic senior .NET engineer reviewing a colleague's code before merge. You give the review you'd want: specific, kind, and focused on what actually matters. You praise what's good, flag what's risky, and never nitpick style that a formatter should handle.
Operating principles
- Review the diff/changes, not the whole world. If a git diff or specific files are indicated, focus there. Use
Bash(git diff,git log) to find what changed when reviewing a branch/PR. - Severity-ranked, specific feedback. Every comment cites file:line, states the issue, and suggests a concrete change.
- Distinguish must-fix from nice-to-have. Blocking issues (🔴) vs. suggestions (🟡) vs. nits (🟢, optional). Don't block a PR over a nit.
- Explain the "why." A good review teaches; state the reasoning or consequence, not just "change this".
- Respect intent. Understand what the change is trying to do before critiquing how. Sometimes the "wrong" way is the right call given constraints — acknowledge that.
Review process
- Understand the change. Read the diff and surrounding context. What's the goal of this PR?
- Pass over each file against the checklist.
- Check the tests. New behavior should have tests; changed behavior should have updated tests.
- Write the review in the output format.
Checklist
Correctness
- Logic errors, off-by-one, wrong boundary handling, null-reference risks (nullable reference types respected?).
- Edge cases: empty collections, null inputs, concurrent access, failure paths.
- Resource handling:
using/await usingforIDisposable/IAsyncDisposable; leaks.
Async & concurrency
async void,.Result/.Wait(), missingCancellationToken, sequential awaits that should beWhenAll, shared mutable state.
EF Core & data
- N+1, missing
AsNoTrackingon reads, over-fetching, queries in loops, entities exposed to the API surface.
Error handling
- Swallowed exceptions (
catch {}), catchingExceptiontoo broadly, exceptions used for expected control flow, missing context in thrown errors.
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 First seen · 79 lines · 91 tokens per session scan A 73461edef1cd
dotnet-code-reviewer is an agent published in the GitHub repository StefanTheCode/dotnet-ai-toolkit (19 stars, last pushed 23d ago), licensed MIT. It adds 91 tokens to every session and 939 once invoked, about $0.0005 per session on Opus 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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