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Find CSteam3ServerS1 InitGameServer Decompiles

Organization
HLND2T
find-CSteam3ServerS1_InitGameServer-decompiles

Final-guarantee fallback for the find-CSteam3ServerS1_InitGameServer-decompiles preprocessor. Recovers the INetworkSystem::GetUDPPort and INetworkServerService::IsActiveInGame indirect virtual-call slots in CS2 engine2.dll / libengine2.so by decompiling CSteam3ServerS1_InitGameServer and following any de-inlined helper. Use when the deterministic/LLM preprocessor could not resolve every call because the containing code moved across an inline boundary. Trigger: INetworkSystem_GetUDPPort, INetworkServerService_IsActiveInGame

Overview

PublisherHLND2T
RepositoryCS2_VibeSignatures
Skill namefind-CSteam3ServerS1_InitGameServer-decompiles
Stars
67
Forks
11
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by HLND2T on GitHub. Read the source before you install it.

Installation

Install the Find CSteam3ServerS1 InitGameServer Decompiles 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/HLND2T/CS2_VibeSignatures/tree/main/.claude/skills/find-CSteam3ServerS1_InitGameServer-decompiles
  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/HLND2T/CS2_VibeSignatures.git /tmp/CS2_VibeSignatures
mkdir -p .claude/skills
cp -r /tmp/CS2_VibeSignatures/.claude/skills/find-CSteam3ServerS1_InitGameServer-decompiles .claude/skills/find-CSteam3ServerS1_InitGameServer-decompiles
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Find CSteam3ServerS1 InitGameServer Decompiles 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 Find CSteam3ServerS1 InitGameServer Decompiles 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 Find CSteam3ServerS1 InitGameServer Decompiles 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.

Find InitGameServer network interface calls (final-guarantee fallback)

Recover every output of find-CSteam3ServerS1_InitGameServer-decompiles in CS2 engine2.dll / libengine2.so using IDA Pro MCP. This Agent fallback runs only after the preprocessor fails, so it must produce any missing output itself while preserving outputs that a partial preprocessor run already wrote.

Realworld Function References

Read the platform-relevant reference YAML before searching in IDA. Its addresses, offsets, and signatures are reference-build values only; verify every result against the current binary.

  • ida_preprocessor_scripts/references/engine/CSteam3ServerS1_InitGameServer.windows.yaml
  • ida_preprocessor_scripts/references/engine/CSteam3ServerS1_InitGameServer.linux.yaml

Background and robustness principle

CSteam3ServerS1_InitGameServer initializes the game-server networking state. It queries two 16-bit UDP ports from the network system, then uses INetworkServerService::IsActiveInGame to select which port to retain. Both targets are indirect virtual calls: their YAML identifies the call instruction and vtable slot, not a concrete function body.

First inspect the predecessor itself. If either call is absent, enumerate its direct callees, decompile plausible helpers, and search one or two levels down: an update may de-inline the networking setup into a helper (or inline it back into the predecessor). Identify calls by their receiver globals and neighboring behavior, never by a fixed function address or call-site address.

Output inventory

Both outputs are required on both platforms. The slot values below were observed in builds 14181 and 14186; derive and verify the current value from the instruction before writing YAML.

Output symbolKindWindows referenceLinux referenceWriter skill
INetworkSystem_GetUDPPortindirect vcallINetworkSystem, 0x118, index 35INetworkSystem, 0x118, index 35/write-vfunc-as-yaml
INetworkServerService_IsActiveInGameindirect vcallCNetworkServerService_vtable, 0xC0, index 24CNetworkServerService_vtable, 0xC8, index 25/write-vfunc-as-yaml

Step 0. Skip outputs already produced

For each output, check whether <symbol>.<platform>.yaml already exists in the active artifact module directory and parses as a non-empty mapping. Skip an existing output: the preprocessor or an earlier fallback may have written it. Use the analyzer-reported artifact module directory, not a path derived from the binary directory.

Step 1. Load and decompile the predecessor

ALWAYS use SKILL /get-func-from-yaml with func_name=CSteam3ServerS1_InitGameServer to obtain func_va. If it fails, stop and report the missing prerequisite. Then decompile that address:

mcp__ida-pro-mcp__decompile addr="<CSteam3ServerS1_InitGameServer.func_va>"

Record calls made by the predecessor so that a missing direct pattern can be followed into de-inlined helpers.

Step 2. Resolve INetworkSystem_GetUDPPort

Locate the indirect call qword ptr [vtable + offset] whose receiver is loaded from g_pNetworkSystem. Its distinguishing semantic pattern is the pair of adjacent g_pNetworkSystem port queries that precede the IsActiveInGame call: the target is the one whose 16-bit result is retained when IsActiveInGame returns true. The other port query (GetBoundUDPPort, normally slot 0x110) is retained when it returns false; do not confuse this target with it or with unrelated +0x118 calls on other receivers.

The current call displacement is the vfunc_offset; calculate vfunc_index = vfunc_offset / 8. The reference value is 0x118 on both platforms, but the receiver must be verified as g_pNetworkSystem in the current binary. Use vtable_name=INetworkSystem.

Step 3. Resolve INetworkServerService_IsActiveInGame

Locate the following indirect vcall whose receiver is loaded from g_pNetworkServerService. It returns a boolean used to choose between the two preceding network-system results, before the SteamGameServer_Init() logging path. This receiver-global/data-flow pairing distinguishes it from other virtual calls nearby.

Derive the current displacement and vfunc_index = vfunc_offset / 8. Reference values are Windows 0xC0 / index 24 and Linux 0xC8 / index 25; do not assume them if the current instruction differs. Use vtable_name=CNetworkServerService_vtable, matching the other INetworkServerService_* slot outputs.

Step 4. Generate signatures and write YAML

For each missing target, use /generate-signature-for-vfuncoffset on the resolved call instruction with its verified vfunc_offset. The vfunc_sig must start at that instruction, include the displacement bytes without wildcards, and be unique in the current binary.

Then use /write-vfunc-as-yaml with:

  • artifact_name: the output symbol's legacy file stem
  • func_name: INetworkSystem_GetUDPPortWithFallback for the INetworkSystem_GetUDPPort artifact; otherwise the output symbol unchanged. This call uses the fallback-port accessor, not the separate bound-port method.
  • func_addr=None and func_sig=None (these are call-slot outputs, not function bodies)
  • vfunc_sig: the generated call-instruction signature
  • vfunc_sig_disp=0 (or omit it)
  • vtable_name: INetworkSystem or CNetworkServerService_vtable as identified above
  • vfunc_offset: the verified instruction displacement
  • vfunc_index: vfunc_offset / 8

Do not rename or resolve a concrete implementation address. The expected YAML contains only func_name, vtable_name, vfunc_offset, vfunc_index, and vfunc_sig.

Failure handling

  • If the predecessor YAML is unavailable, stop and report it.
  • If a required call is missing from the predecessor, follow its plausible callees before declaring it unresolved.
  • If one target remains unresolved, write any other verified missing target, then report exactly which output failed.
  • Never write a Windows output while analyzing Linux, or vice versa.

Output YAML filenames

Write under the active artifact module directory:

  • INetworkSystem_GetUDPPort.windows.yaml / INetworkSystem_GetUDPPort.linux.yaml
  • INetworkServerService_IsActiveInGame.windows.yaml / INetworkServerService_IsActiveInGame.linux.yaml

Frequently asked questions

What does the Find CSteam3ServerS1 InitGameServer Decompiles AI skill do?

Final-guarantee fallback for the find-CSteam3ServerS1_InitGameServer-decompiles preprocessor. Recovers the INetworkSystem::GetUDPPort and INetworkServerService::IsActiveInGame indirect virtual-call slots in CS2 engine2.dll / libengine2.so by decompiling CSteam3ServerS1_InitGameServer and following any de-inlined helper. Use when the deterministic/LLM preprocessor could not resolve every call because the containing code moved across an inline boundary. Trigger: INetworkSystem_GetUDPPort, INetworkServerService_IsActiveInGame

Why use Find CSteam3ServerS1 InitGameServer Decompiles on TypingMind?

Because you install it once and use it with any model. Find CSteam3ServerS1 InitGameServer Decompiles 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 Find CSteam3ServerS1 InitGameServer Decompiles in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/HLND2T/CS2_VibeSignatures/tree/main/.claude/skills/find-CSteam3ServerS1_InitGameServer-decompiles. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Find CSteam3ServerS1 InitGameServer Decompiles?

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 Find CSteam3ServerS1 InitGameServer Decompiles?

As many as you like. As long as a model supports skills, you can use Find CSteam3ServerS1 InitGameServer Decompiles with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Find CSteam3ServerS1 InitGameServer Decompiles AI skill free?

Yes. It is published on GitHub by HLND2T 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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