Dotnet Debugging logo

Dotnet Debugging

Organization
novotnyllc
dotnet-debugging

Debugs Windows and Linux/macOS applications (native, .NET/CLR, mixed-mode) with WinDbg MCP (crash dumps, !analyze, !syncblk, !dlk, !runaway, !dumpheap, !gcroot, BSOD), dotnet-dump, lldb with SOS, createdump, and container diagnostics (Docker, Kubernetes). Hang/deadlock diagnosis, high CPU triage, memory leak investigation, kernel debugging, and dotnet-monitor for production. Spans 17 topic areas. Do not use for routine .NET SDK profiling, benchmark design, or CI test debugging.

Overview

Publishernovotnyllc
Repositorydotnet-artisan
Skill namedotnet-debugging
Stars
235
Forks
14
Bundled files
18
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 18 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by novotnyllc on GitHub. Read the source before you install it.

Installation

Install the Dotnet Debugging AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/novotnyllc/dotnet-artisan/tree/main/plugins/dotnet-artisan/skills/dotnet-debugging
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/novotnyllc/dotnet-artisan.git /tmp/dotnet-artisan
mkdir -p .claude/skills
cp -r /tmp/dotnet-artisan/plugins/dotnet-artisan/skills/dotnet-debugging .claude/skills/dotnet-debugging
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dotnet Debugging in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Dotnet Debugging on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Dotnet Debugging is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

dotnet-debugging

Overview

Windows and Linux/macOS debugging using WinDbg MCP tools (Windows), dotnet-dump, and lldb with SOS (Linux/macOS). Applicable to any application -- native, managed (.NET/CLR), or mixed-mode. Includes container diagnostic patterns for Docker and Kubernetes. Guides investigation of crash dumps, application hangs, high CPU, and memory pressure through structured command packs and report templates.

Platforms: Windows (WinDbg MCP, cdb), Linux/macOS (dotnet-dump, lldb with SOS, createdump, dotnet-monitor).

Routing Table

TopicKeywordsDescriptionCompanion File
MCP setupMCP server, WinDbg, configurationMCP server configurationreferences/mcp-setup.md
MCP accessMCP access, tool IDs, dispatchMCP access patternsreferences/access-mcp.md
Common patternsdebug patterns, SOS, CLRCommon debugging patternsreferences/common-patterns.md
Dump workflowdump file, .dmp, crash dumpDump file analysis workflowreferences/dump-workflow.md
Live attachlive process, cdb, attachLive process attach guidereferences/live-attach.md
Symbolssymbol server, .symfix, PDBSymbol configurationreferences/symbols.md
Sanity checkverify, environment, baselineSanity check proceduresreferences/sanity-check.md
Scenario packscommand pack, triage, workflowScenario command packsreferences/scenario-command-packs.md
Capture playbookscapture, procdump, triggersCapture playbooksreferences/capture-playbooks.md
Report templatediagnostic report, evidenceDiagnostic report templatereferences/report-template.md
Crash triagecrash, exception, access violationCrash triagereferences/task-crash.md
Hang triagehang, deadlock, freezeHang triagereferences/task-hang.md
High-CPU triagehigh CPU, runaway thread, spinHigh-CPU triagereferences/task-high-cpu.md
Memory triagememory leak, heap, LOHMemory leak triagereferences/task-memory.md
Kernel debuggingkernel, BSOD, bugcheckKernel debuggingreferences/task-kernel.md
Unknown triageunknown issue, general triageUnknown issue triagereferences/task-unknown.md
Linux debuggingdotnet-dump, lldb, createdump, containerLinux/macOS debugging, dotnet-dump, lldb SOS, containersreferences/linux-debugging.md

Scope

  • Crash dump analysis (.dmp files) on Windows, Linux, and macOS
  • Live process attach (cdb on Windows, lldb on Linux/macOS)
  • Hang and deadlock diagnosis (thread analysis, lock detection, wait chains)
  • High CPU triage (runaway thread identification)
  • Memory pressure and leak investigation (managed heap, native heap)
  • Kernel dump triage (BSOD / bugcheck analysis, Windows)
  • Container diagnostics (dotnet-dump in Docker/Kubernetes, sidecar patterns)
  • Production diagnostics (dotnet-monitor REST API, trigger-based collection)
  • SOS commands across all platforms (WinDbg, dotnet-dump, lldb)
  • Structured diagnostic reports with stack evidence

Boundary with dotnet-tooling

Both skills use overlapping tools (dotnet-dump, dotnet-counters, dotnet-trace) but for different purposes:

ScenarioUse this skill (debugging)Use dotnet-tooling
Investigating a crash dump (.dmp)YesNo
"Why did my app crash/hang/OOM?"YesNo
Attaching a debugger to a live processYesNo
"How do I profile my app's performance?"NoYes (profiling)
"How do I reduce GC pressure?"NoYes (gc-memory)
Collecting a dump for later analysisYesNo
Running dotnet-counters to monitor metricsNoYes (profiling)
Analyzing a dump with dotnet-dumpYesNo
Decompiling an assembly to understand behaviorNoYes (ilspy-decompile)

Rule of thumb: if something is broken (crash, hang, deadlock, OOM), route here. If something is slow or needs optimization, route to dotnet-tooling.

Out of scope

  • Performance profiling (dotnet-counters, dotnet-trace for optimization) -> dotnet-tooling
  • GC tuning and managed memory optimization -> dotnet-tooling
  • Assembly decompilation (ILSpy) -> dotnet-tooling
  • Performance benchmarking and regression detection -> dotnet-testing
  • Application-level logging and observability -> dotnet-devops
  • Unit/integration test debugging -> dotnet-testing

MCP Tool Contract

These tool IDs are the WinDbg MCP server's exported names (single-underscore mcp_...), not the mcp__... dispatch prefix used by some hosts.

OperationPurpose
mcp_mcp-windbg_open_windbg_remoteAttach to a live debug server
mcp_mcp-windbg_open_windbg_dumpOpen a saved dump file
mcp_mcp-windbg_run_windbg_cmdExecute debugger commands
mcp_mcp-windbg_close_windbg_remoteDetach from live session
mcp_mcp-windbg_close_windbg_dumpClose dump session

Diagnostic Workflow

Preflight: Symbols

Before any analysis, configure symbols to get meaningful stacks:

  1. Set Microsoft symbol server: .symfix (sets srv* to Microsoft public symbols)
  2. Add application symbols: .sympath+ C:\path\to\your\pdbs
  3. Reload modules: .reload /f
  4. Verify: lm (list modules -- check for "deferred" vs "loaded" status)

Without correct symbols, stacks show raw addresses instead of function names.

Crash Dump Analysis

  1. Open dump: mcp_mcp-windbg_open_windbg_dump with dump file path
  2. Load SOS for managed code: .loadby sos clr (Framework) or .loadby sos coreclr (.NET Core)
  3. Get exception context: !pe (print exception), !analyze -v (automatic analysis)
  4. Inspect threads: ~*e !clrstack (all managed stacks), !threads (thread list)
  5. Check managed heap: !dumpheap -stat (heap summary), !gcroot <addr> (object roots)

Hang / Deadlock Diagnosis

  1. Attach or open dump, load SOS
  2. List all threads: !threads, identify waiting threads with !syncblk (sync block table)
  3. Detect deadlocks: !dlk (SOS deadlock detection)
  4. Inspect thread stacks: ~Ns !clrstack for specific thread N
  5. Check wait reasons: !waitchain for COM/RPC chains, !mda for MDA diagnostics

High CPU Triage

  1. Attach to live process or collect multiple dumps 10-30 seconds apart
  2. Use !runaway to identify threads consuming the most CPU time
  3. Inspect hot thread stacks: ~Ns kb (native stack), ~Ns !clrstack (managed stack)
  4. Look for tight loops, blocked finalizer threads, or excessive GC

Memory Pressure Investigation

  1. Open dump, load SOS
  2. Managed heap: !dumpheap -stat (type statistics), !dumpheap -type <TypeName> (filter)
  3. Find leaked objects: !gcroot <address> (trace GC roots to pinned or static references)
  4. Native heap: !heap -s (heap summary), !heap -l (leak detection)
  5. LOH fragmentation: !eeheap -gc (GC heap segments)

Report Template

## Diagnostic Report

**Symptom:** [crash/hang/high-cpu/memory-leak]
**Process:** [name, PID, bitness]
**Dump type:** [full/mini/live-attach]

### Evidence
- Exception: [type and message, or N/A]
- Faulting thread: [ID, managed/native, stack summary]
- Key stacks: [condensed callstack with module!function]

### Root Cause
[Concise analysis backed by stack/heap evidence]

### Recommendations
[Numbered action items]

Guardrails

  • Do not claim certainty without callee-side evidence
  • Do not call it a deadlock unless lock/wait evidence supports it
  • Preserve user privacy: do not include secrets from environment blocks in reports

Cross-references: dotnet-tooling for .NET SDK diagnostic tools (references/profiling.md) and GC/memory tuning (references/gc-memory.md).

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dotnet Debugging AI skill do?

Debugs Windows and Linux/macOS applications (native, .NET/CLR, mixed-mode) with WinDbg MCP (crash dumps, !analyze, !syncblk, !dlk, !runaway, !dumpheap, !gcroot, BSOD), dotnet-dump, lldb with SOS, createdump, and container diagnostics (Docker, Kubernetes). Hang/deadlock diagnosis, high CPU triage, memory leak investigation, kernel debugging, and dotnet-monitor for production. Spans 17 topic areas. Do not use for routine .NET SDK profiling, benchmark design, or CI test debugging.

Why use Dotnet Debugging on TypingMind?

Because you install it once and use it with any model. Dotnet Debugging is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Dotnet Debugging in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/novotnyllc/dotnet-artisan/tree/main/plugins/dotnet-artisan/skills/dotnet-debugging. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dotnet Debugging?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Dotnet Debugging?

As many as you like. As long as a model supports skills, you can use Dotnet Debugging with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Dotnet Debugging AI skill free?

Yes. It is published on GitHub by novotnyllc under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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