Find CNetworkGameServerBase CreateFakeClient logo

Find CNetworkGameServerBase CreateFakeClient

Organization
HLND2T
find-CNetworkGameServerBase_CreateFakeClient

Final-guarantee fallback for the find-CNetworkGameServerBase_CreateFakeClient preprocessor. Recovers CNetworkGameServerBase_CreateFakeClient in CS2 engine2.dll / libengine2.so when the string-xref preprocessor cannot resolve the function. Use this skill only after the deterministic preprocessor returns failure. Trigger: CNetworkGameServerBase_CreateFakeClient

Overview

PublisherHLND2T
RepositoryCS2_VibeSignatures
Skill namefind-CNetworkGameServerBase_CreateFakeClient
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 CNetworkGameServerBase CreateFakeClient 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-CNetworkGameServerBase_CreateFakeClient
  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-CNetworkGameServerBase_CreateFakeClient .claude/skills/find-CNetworkGameServerBase_CreateFakeClient
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Find CNetworkGameServerBase CreateFakeClient 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 CNetworkGameServerBase CreateFakeClient 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 CNetworkGameServerBase CreateFakeClient 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 CNetworkGameServerBase_CreateFakeClient (final-guarantee fallback)

Recover the concrete CNetworkGameServerBase_CreateFakeClient function in CS2 engine2.dll / libengine2.so using IDA Pro MCP tools. This is an Agent fallback: it runs only when ida_preprocessor_scripts/find-CNetworkGameServerBase_CreateFakeClient.py cannot resolve the target.

Realworld Function References

The finder has no dedicated predecessor reference YAML. Use these related references for the class and calling conventions; their addresses and offsets are reference-build values and must be verified against the current binary.

  • ida_preprocessor_scripts/references/engine/CNetworkGameServerBase_Init.windows.yaml
  • ida_preprocessor_scripts/references/engine/CNetworkGameServerBase_Init.linux.yaml
  • ida_preprocessor_scripts/references/engine/CNetworkGameServerBase_ConnectClient.windows.yaml
  • ida_preprocessor_scripts/references/engine/CNetworkGameServerBase_ConnectClient.linux.yaml

Semantic fingerprint

CNetworkGameServerBase_CreateFakeClient is a member of CNetworkGameServerBase that creates and initializes a fake network client. The deterministic finder anchors it with both exact string references 30000 and rate. Those literals identify the rate initialization in the target or in a small helper it calls; do not identify the function from either literal alone.

The first argument is the server object (rcx on Windows, usually rdi/r12 on Linux). Confirm that the candidate allocates or initializes a client and that the 30000/rate values belong to that initialization path, not to an unrelated command or diagnostic routine.

Step 0. Skip an existing output

If CNetworkGameServerBase_CreateFakeClient.<platform>.yaml already exists in the active artifact module directory and parses to a non-empty mapping, skip that platform. Never derive the artifact path from bin.

Step 1. Locate the target in IDA

  1. Search the current binary for the exact string literals 30000 and rate (including command-table or format string variants), then enumerate their code xrefs.
  2. Decompile each function that references both anchors. Prefer the candidate whose first parameter is the CNetworkGameServerBase object and whose body creates a client, sets its connection/rate state, or calls the client initialization helper.
  3. If the two strings occur in a helper, follow callers and callees one level in each direction until the containing CNetworkGameServerBase member is identified. The helper may be inlined or outlined on either platform, so use the client-construction and rate-initialization semantics rather than a fixed address.
  4. Reject candidates that only register a console command, format a message, or initialize an unrelated rate.

The reference artifacts for build 14167 are only orientation values (verify every field against the current binary):

PlatformReference func_vaReference func_rvaReference size
Windows0x1800af8400xaf8400x24d
Linux0x6968d00x6968d00x2b8

Step 2. Generate the signature and write YAML

After confirming the candidate:

  1. Use SKILL /generate-signature-for-function with the resolved function address. The signature must be generated from the current function body and pass its uniqueness checks.
  2. Use SKILL /write-func-as-yaml with:
    • func_name=CNetworkGameServerBase_CreateFakeClient
    • func_addr=<resolved address>
    • func_rva=<resolved address minus image base>
    • func_size=<current function size>
    • func_sig=<validated signature>

Write one output per input platform:

  • CNetworkGameServerBase_CreateFakeClient.windows.yaml beside engine2.dll
  • CNetworkGameServerBase_CreateFakeClient.linux.yaml beside libengine2.so

Failure handling

  • If no candidate references both semantic anchors, inspect nearby callers/callees and decompiled client creation helpers before stopping.
  • If the candidate cannot be distinguished from an unrelated rate-setting routine, stop and report the ambiguity; do not guess from the 14167 values.
  • Never emit a Windows result while analyzing Linux or vice versa.

Frequently asked questions

What does the Find CNetworkGameServerBase CreateFakeClient AI skill do?

Final-guarantee fallback for the find-CNetworkGameServerBase_CreateFakeClient preprocessor. Recovers CNetworkGameServerBase_CreateFakeClient in CS2 engine2.dll / libengine2.so when the string-xref preprocessor cannot resolve the function. Use this skill only after the deterministic preprocessor returns failure. Trigger: CNetworkGameServerBase_CreateFakeClient

Why use Find CNetworkGameServerBase CreateFakeClient on TypingMind?

Because you install it once and use it with any model. Find CNetworkGameServerBase CreateFakeClient 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 CNetworkGameServerBase CreateFakeClient in TypingMind?

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

Which AI models can use Find CNetworkGameServerBase CreateFakeClient?

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 CNetworkGameServerBase CreateFakeClient?

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

Is the Find CNetworkGameServerBase CreateFakeClient 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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