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.
npx skills add HLND2T/CS2_VibeSignatures --skill find-onservervoicedata_isplayingdemo_calleegit clone --depth 1 https://github.com/HLND2T/CS2_VibeSignaturesWrote 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/skills/hlnd2t/cs2_vibesignatures/find-onservervoicedata_isplayingdemo_callee)<a href="https://agentmods.dev/skills/hlnd2t/cs2_vibesignatures/find-onservervoicedata_isplayingdemo_callee"><img src="https://agentmods.dev/badge/skills/hlnd2t/cs2_vibesignatures/find-onservervoicedata_isplayingdemo_callee/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/skills/hlnd2t/cs2_vibesignatures/find-onservervoicedata_isplayingdemo_callee"><img src="https://agentmods.dev/badge/skills/hlnd2t/cs2_vibesignatures/find-onservervoicedata_isplayingdemo_callee.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00099 | $0.00763 |
| Opus 5.5 | $0.00040 | $0.00305 |
| Sonnet 5.5 | $0.00020 | $0.00153 |
| Haiku 4.5 | $0.00010 | $0.00076 |
Grade A, and why
find-OnServerVoiceData_IsPlayingDemo_Callee 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 2mo 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 — 93 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OnServerVoiceData_IsPlayingDemo_Callee Patch Workflow
Overview
This Windows-only patch finder converts the already-generated
IVEngineClient2_IsPlayingDemo.windows.yaml vfunc metadata into
OnServerVoiceData_IsPlayingDemo_Callee.windows.yaml.
The target call site is inside C_ServerVoiceHandler::OnServerVoiceData:
mov rcx, cs:g_pSource2EngineToClient
mov rax, [rcx]
call qword ptr [rax+150h] ; IVEngineClient2::IsPlayingDemo
test al, al
jz short loc_...
The patch address is the address of the indirect call instruction itself.
Prerequisite
The following input YAML must already exist in the current client module output directory:
IVEngineClient2_IsPlayingDemo.windows.yaml
Its required fields are:
func_name: IVEngineClient2_IsPlayingDemo
vtable_name: IVEngineClient2
vfunc_offset: '0x150'
vfunc_index: 42
vfunc_sig: FF 90 50 01 00 00 84 C0 74 ?? 83 FD ??
Deterministic Preprocessor
Run through the configured ida_analyze_bin.py pipeline. The corresponding script is:
ida_preprocessor_scripts/find-OnServerVoiceData_IsPlayingDemo_Callee.py
The script performs these checks without LLM invocation:
- Rejects every platform except Windows.
- Reads the input vfunc YAML from the current client output directory.
- Verifies the function name, vtable name, and
vfunc_offset / 8 == vfunc_indexrelationship. - Verifies that
vfunc_sigstarts with the concrete encoding ofcall qword ptr [rax+vfunc_offset]. - Calls IDA MCP
find_byteswith the fullvfunc_sigand requires exactly one match. - Writes the match address as
patch_va, derivespatch_rvafrom the image base, copiesvfunc_sigtopatch_sig, and writespatch_sig_disp: 0.
Output
For game version 14173, the expected output is:
patch_name: OnServerVoiceData_IsPlayingDemo_Callee
patch_va: '0x180aec45d'
patch_rva: '0xaec45d'
patch_sig: FF 90 50 01 00 00 84 C0 74 ?? 83 FD ??
patch_sig_disp: 0
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.
- 2mo ago First seen · 93 lines · 99 tokens per session scan A 252aff6f6fbe
find-OnServerVoiceData_IsPlayingDemo_Callee is a skill published in the GitHub repository HLND2T/CS2_VibeSignatures (67 stars, last pushed today), licensed MIT. It adds 99 tokens to every session and 763 once invoked, about $0.0004 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 2026-08-30.
find-OnServerVoiceData_IsPlayingDemo_Callee compared with skills from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| find-OnServerVoiceData_IsPlayingDemo_CalleeHLND2T/CS2_VibeSignatures | Skill | 67 | today | MIT | A | 99 | Claude Code |
| imagegenopenai/codex | Skill | 133k | yesterday | Apache-2.0 | A | 113 | Codex |
| playwright-climicrosoft/playwright | Skill | 99k | yesterday | Apache-2.0 | A | 19 | Claude Code |
| local-ai-agentsmicrosoft/ai-agents-for-beginners | Skill | 79k | 4d ago | MIT | A | 200 | Claude Code, Codex |
| systematic-debuggingobra/superpowers | Skill | 313k | 3d ago | MIT | A | 21 | Claude Code |
| next-cache-components-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 95 | Claude Code |
| next-partial-prefetching-adoptionvercel/next.js | Skill | 143k | today | MIT | A | 103 | Claude Code |