Find GetCSWeaponDataFromKey Inlined logo

Find GetCSWeaponDataFromKey Inlined

Organization
HLND2T
find-GetCSWeaponDataFromKey-inlined

Recover GetCSWeaponDataFromKey in CS2 server binaries (Windows and Linux) when the find-GetCSWeaponDataFromKey-inlined preprocessor fails. Verify current string-key weapon lookup semantics rather than reusing historical addresses or signatures. Trigger: GetCSWeaponDataFromKey

Overview

PublisherHLND2T
RepositoryCS2_VibeSignatures
Skill namefind-GetCSWeaponDataFromKey-inlined
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 GetCSWeaponDataFromKey Inlined 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-GetCSWeaponDataFromKey-inlined
  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-GetCSWeaponDataFromKey-inlined .claude/skills/find-GetCSWeaponDataFromKey-inlined
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Find GetCSWeaponDataFromKey Inlined 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 GetCSWeaponDataFromKey Inlined 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 GetCSWeaponDataFromKey Inlined 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 GetCSWeaponDataFromKey (Agent fallback)

Recover the single output of find-GetCSWeaponDataFromKey-inlined using the assigned IDA Pro MCP database. The preprocessor ida_preprocessor_scripts/find-GetCSWeaponDataFromKey-inlined.py remains the normal fast path.

Realworld Function References

Read the applicable current inputs and the annotated references below. Source-owned 14192 YAMLs and stored disassembly are reference-build evidence; verify addresses, slot indices and semantics in the assigned binary. Never copy a reference target YAML into the active output directory as a substitute for analysis.

  • ida_preprocessor_scripts/references/server/CSmokeGrenadeProjectile_Create.windows.yaml
  • ida_preprocessor_scripts/references/server/CSmokeGrenadeProjectile_Create.linux.yaml
  • bin_artifacts/14192/server/CSmokeGrenadeProjectile_Create.windows.yaml
  • bin_artifacts/14192/server/CSmokeGrenadeProjectile_Create.linux.yaml

Output inventory

Module: server. Platform scope: Windows and Linux. Analyze only the platform of the assigned database; the runner invokes platforms separately.

PlatformOutput filename14192 reference entryReference slot / offset
windowsGetCSWeaponDataFromKey.windows.yaml0x1805506f0not a vfunc
linuxGetCSWeaponDataFromKey.linux.yaml0xef8b80not a vfunc

This is a regular function, with no vtable metadata. Generate a validated function signature after identifying the current entry.

Step 0. Bind the task and skip an existing output

Call idb_list and reuse the database assigned by the runner. Confirm the input path, image base and platform with IDA; do not open, switch, close or quit the runner's database. The binary is server.dll / libserver.so. Resolve the active artifact module directory from CS2VIBE_ARTIFACT_DIR (also visible inside IDA's environment). If unset, stop and request the assigned artifact directory; never write YAML beside the binary. For the current platform, skip the output if it already exists there and parses as a non-empty mapping. Do not overwrite a result produced by an earlier alternative.

Load the platform-specific configured inputs named above from that active artifact root, not from the 14192 reference tree. Resolve ../client or ../server relative to the active module directory. Missing required inputs must be reported; do not open another binary to reconstruct them.

Step 1. Locate and verify the target

Use /get-func-from-yaml with func_name=CSmokeGrenadeProjectile_Create. Decompile and inspect the current Create body. Follow the weapon/item-definition lookup branch, then inspect its direct calls and any actual intermediate wrapper; stop after the lookup's semantics are established instead of blindly following a fixed number of calls.

The desired function accepts a data type and a STRING key, guards the string, hashes it, looks up weapon data and checks the type. For the smoke call, type is 1: ECX=1 and string in RDX on Windows; EDI=1 and string in RSI on Linux. Murmur landmarks are seed 0x31415926 and multiplier 0x5BD1E995. Linux commonly inlines hashing; Windows may pass the seed to a separate directly called hash routine, so inspect that callee for the multiplier. Treat the constants plus argument dataflow as evidence, not constants alone.

The old CSmokeGrenadeProjectile_GetCSWeaponData intermediate may be inlined. Its current legacy YAML may already point to the final string lookup; verify the emitted func_name and body before descending again. Reject the internal table/type/HASH lookup (14192 Linux reference 0xef8320), which takes a numeric hash rather than the source string. Also reject the unrelated coordinate-update routine previously mislabeled as the Windows smoke helper (14192 reference 0x1809d6140). The verified final string lookup is the desired output whether Create reaches it directly or through a real wrapper.

Signatures and YAML output

Use /generate-signature-for-function on the verified current entry. Validate uniqueness in the assigned binary; do not copy the baseline signature. Keep the finder's existing generation options: these targets do not enable func_sig_allow_across_function_boundary, func_sig_resolve_jmp_thunk or func_sig_skip_degenerate; do not add those directives. If the fully wildcarded head is ambiguous, compare the competing matches and refine only distinguishing wildcard bytes within the verified function body, following the canonical refinement in ida_analyze_util.preprocess_gen_func_sig_via_mcp. Revalidate the pattern at the exact entry. If no valid unique body signature can be obtained, report the unresolved output instead of extending into neighbouring functions. Use /write-func-as-yaml through its IDA py_eval implementation in the assigned session to write the YAML; do not substitute CLI shell or file-edit tools. Parameters:

  • artifact_name=GetCSWeaponDataFromKey and func_name=GetCSWeaponDataFromKey.

  • func_addr: the verified concrete entry in the assigned binary; emit func_va, func_rva = VA - image_base and the verified current func_size. Never emit a bodyless slot-only result for this target.

  • func_sig: the validated current function signature.

Write only GetCSWeaponDataFromKey.windows.yaml / GetCSWeaponDataFromKey.linux.yaml as applicable, under the active artifact module directory. The trusted analyzer validates and canonicalizes this semantic payload. Read back the output and verify its name, fields, slot (when applicable), RVA and platform against the live database before reporting success.

Failure handling

If required inputs are missing, candidates remain ambiguous, entry recovery is unsafe, or no standalone entry can be verified, stop and report the exact missing output plus the semantic evidence examined. Do not invent a signature/address, create a placeholder YAML, disable config entries, or claim that a failed lookup proves the game removed the function. Do not run the failed preprocessor as the fallback's solution.

Frequently asked questions

What does the Find GetCSWeaponDataFromKey Inlined AI skill do?

Recover GetCSWeaponDataFromKey in CS2 server binaries (Windows and Linux) when the find-GetCSWeaponDataFromKey-inlined preprocessor fails. Verify current string-key weapon lookup semantics rather than reusing historical addresses or signatures. Trigger: GetCSWeaponDataFromKey

Why use Find GetCSWeaponDataFromKey Inlined on TypingMind?

Because you install it once and use it with any model. Find GetCSWeaponDataFromKey Inlined 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 GetCSWeaponDataFromKey Inlined in TypingMind?

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

Which AI models can use Find GetCSWeaponDataFromKey Inlined?

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 GetCSWeaponDataFromKey Inlined?

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

Is the Find GetCSWeaponDataFromKey Inlined 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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