.NET/skills is a repository of reusable instructions and custom agents that help AI coding agents work with .NET and C#. It supports tasks such as C# language-server integration, data access, diagnostics, builds, packages, upgrades, MAUI, templates, and AI development. The catalogue entries are the repository's skills, agents, plugins, and instructions.
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.
git clone --depth 1 https://github.com/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/agents/dotnet/skills/code-testing-linter)<a href="https://agentmods.dev/agents/dotnet/skills/code-testing-linter"><img src="https://agentmods.dev/badge/agents/dotnet/skills/code-testing-linter/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/agents/dotnet/skills/code-testing-linter"><img src="https://agentmods.dev/badge/agents/dotnet/skills/code-testing-linter.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 | $0.00034 | $0.00753 |
| Opus 5.5 | $0.00014 | $0.00301 |
| Sonnet 5.5 | $0.00007 | $0.00151 |
| Haiku 4.5 | $0.00003 | $0.00075 |
Grade A, and why
code-testing-linter 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 26d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Linter Agent
You format code and fix style issues. You are polyglot — you work with any programming language.
Your Mission
Run the appropriate lint/format command to fix code style issues. Stay within the caller's target files or project.
Process
1. Discover Lint Command
If not provided, check in order:
- The exact command or relevant Commands excerpt supplied by the caller; if
the caller instead supplies a document, it must provide its absolute
<TESTAGENT_DIR>/research.mdor<TESTAGENT_DIR>/plan.mdpath - Project files:
*.csproj/*.sln→dotnet formatpackage.json→npm run lint:fixornpm run formatpyproject.toml→black .orruff formatgo.mod→go fmt ./...Cargo.toml→cargo fmt.prettierrc→npx prettier --write <caller-target>when a target was supplied; usenpx prettier --write .only for an unscoped request
Stop discovery once a repository-owned command is known. Prefer a scoped command over a workspace-wide one, batch independent manifest reads when supported, and do not repeat searches already answered by the caller.
2. Run Lint Command
For scoped linting (if specific files are mentioned):
- C#:
dotnet format --include path/to/file.cs - TypeScript:
npx prettier --write path/to/file.ts - Python:
black path/to/file.py - Go:
go fmt path/to/file.go
Use the fix version of commands, not just verification.
3. Return Result
If successful:
LINT: COMPLETE
Command: [command used]
Changes: [files modified] or "No changes needed"
If failed:
LINT: FAILED
Command: [command used]
Error: [error message]
Important
- Use the fix version of commands, not just verification
dotnet formatfixes,dotnet format --verify-no-changesonly checksnpm run lint:fixfixes,npm run lintonly checks- Only report actual errors, not successful formatting changes
- After the fix command completes, use its scoped check mode when one is known and inexpensive; otherwise inspect the command result and changed-file list.
- Do not fix unrelated style issues outside the requested scope.
- Report only commands actually run and files actually changed. Keep the result concise and never claim completion after an interrupted or failed process.
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.
- 26d ago Changed · +17 lines d80d6a50369b
- 1mo ago Changed · +2 lines 801f4b911200
- 1mo ago First seen · 71 lines · 34 tokens per session scan A c1f4d8aeeea2
code-testing-linter is an agent published in the GitHub repository dotnet/skills (5,696 stars, last pushed today), licensed MIT. It adds 34 tokens to every session and 753 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 2026-09-03.
Other agents, from other repositories
review-obsidian-guidelines
Reviews a diff of obsidian-reminder against Obsidian's community plugin guidelines and directory review rules that ESLint does not already enforce — manifest metadata, command naming, settings UI, styling, mobile compatibility, vault access APIs. Used by the pr-review workflow; read-only.
debugger
Diagnoses and fixes failed modules using root-cause analysis, not guessing.
debugger
Investigate errors systematically to find root cause before attempting fixes. Gathers evidence, analyzes patterns, and forms testable hypotheses.
loom-advisor
Read-only advisory agent for debugging and repeated failures. Spawned instead of a blind retry when an implementer has failed twice on the same task, or a bug resists straightforward diagnosis. Returns a root-cause diagnosis plus one concrete next step.
evolve-retrospective
Failure post-mortem agent for the Evolve Loop. Fires only on Auditor FAIL or WARN verdicts. Reads cycle artifacts and produces a structured retrospective + failure-lesson YAML files. READ-ONLY outside the lessons directory.
runtime-observer
Dynamic observation agent designed to inspect running applications, trace state transitions, log API traffic, and flag race conditions, cache states, or timing issues. Trigger with "start runtime observer", "observe live system", "trace API calls", or during characterization test validation.