CS2_VibeSignatures: Skill for Claude Code

.claude/skills/write-vtable-as-yaml/SKILL.md

write-vtable-as-yaml is a skill for Claude Code from HLND2T/CS2_VibeSignatures. It costs 42 tokens per session (1,728 once invoked), scanned A, original, MIT.

A procedure for saving information about a program’s virtual function table in a YAML file next to its binary, using IDA Pro. A virtual function table stores links to a class’s dynamically selected methods.

In plain words
What is it for?
Use it after locating a virtual function table and identifying its class, so the result is written in a consistent YAML format.
Why use it?
It preserves the class name, table address, and optional symbol in a standard file instead of keeping the result only in the analysis session.

Skill for Claude Code

Written for Claude Code: installed under .claude/.

This is HLND2T/CS2_VibeSignatures's own configuration. It tells Claude Code how to work on CS2_VibeSignatures itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything CS2_VibeSignatures configures →

Reuse

Borrowing it

Nothing to install: this file belongs to HLND2T/CS2_VibeSignatures. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file
curl -O https://raw.githubusercontent.com/HLND2T/CS2_VibeSignatures/main/.claude/skills/write-vtable-as-yaml/SKILL.md
Clone the repo
git clone --depth 1 https://github.com/HLND2T/CS2_VibeSignatures

Made for: Claude Code.

Wrote 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.

agentmods badge for write-vtable-as-yaml

README.md
[![agentmods](https://agentmods.dev/badge/skills/hlnd2t/cs2_vibesignatures/write-vtable-as-yaml/github.svg)](https://agentmods.dev/skills/hlnd2t/cs2_vibesignatures/write-vtable-as-yaml)
Your own site
<a href="https://agentmods.dev/skills/hlnd2t/cs2_vibesignatures/write-vtable-as-yaml"><img src="https://agentmods.dev/badge/skills/hlnd2t/cs2_vibesignatures/write-vtable-as-yaml/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.

agentmods 80×15 button for write-vtable-as-yaml

Your own site · 80×15
<a href="https://agentmods.dev/skills/hlnd2t/cs2_vibesignatures/write-vtable-as-yaml"><img src="https://agentmods.dev/badge/skills/hlnd2t/cs2_vibesignatures/write-vtable-as-yaml.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 42 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,728 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00042 $0.01728
Opus 5 $0.00021 $0.00864
Sonnet 5 $0.00008 $0.00346
Haiku 4.5 $0.00004 $0.00173

Measured 3d ago against content hash ba7c10a027df, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

write-vtable-as-yaml 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 3d 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.

.claude/skills/write-vtable-as-yaml/SKILL.md · 174 lines

How it starts

The opening of the file, as written. The whole thing — 174 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Write VTable as YAML

Persist vtable analysis results to a YAML file beside the binary using IDA Pro MCP.

Prerequisites

Before using this skill, you should have:

  1. Located the target vtable address
  2. Identified the class name for the vtable

Required Parameters

Parameter Description Example
vtable_class Class name for the vtable CSource2Server
vtable_va Virtual address of the vtable 0x182B8D9D8

Optional Parameters

Parameter Description Example
vtable_symbol The IDA symbol name for the vtable "??_7CBaseEntity@@6B@"

Method

mcp__ida-pro-mcp__py_eval code="""
import idaapi
import ida_bytes
import ida_name
import os
import yaml

# === REQUIRED: Replace these values ===
vtable_class = "<vtable_class>"     # e.g., "CBaseEntity"
vtable_va = <vtable_va>             # e.g., 0x182B8D9D8
# ======================================

# === OPTIONAL: Replace these values ===
vtable_symbol = "<vtable_symbol>"     # e.g., "??_7CBaseEntity@@6B@" or "_ZTV11CBaseEntity + 0x10" or "off_180XXXXXX"
# ======================================

input_file = idaapi.get_input_file_path()
dir_path = os.environ.get('CS2VIBE_ARTIFACT_DIR') or os.path.dirname(input_file)

if input_file.endswith('.dll'):
    platform = 'windows'
    image_base = idaapi.get_imagebase()
else:
    platform = 'linux'
    image_base = 0x0

vtable_rva = vtable_va - image_base

# Handle Linux vtables (skip RTTI metadata)
vtable_name = ida_name.get_name(vtable_va) or ""
if vtable_name.startswith("_ZTV"):
    vtable_va = vtable_va + 0x10
    vtable_rva = vtable_va - image_base

# Determine pointer size and count virtual functions
ptr_size = 8 if idaapi.inf_is_64bit() else 4
vtable_entries = []

for i in range(1000):
    if ptr_size == 8:
        ptr_value = ida_bytes.get_qword(vtable_va + i * ptr_size)
    else:
        ptr_value = ida_bytes.get_dword(vtable_va + i * ptr_size)

    if ptr_value == 0 or ptr_value == 0xFFFFFFFFFFFFFFFF:
        break

    func = idaapi.get_func(ptr_value)
    if func is None:
        flags = ida_bytes.get_full_flags(ptr_value)
        if not ida_bytes.is_code(flags):
            break

    vtable_entries.append(ptr_value)

count = len(vtable_entries)
vtable_size = count * ptr_size

# Build YAML data structure
yaml_data = {
    'vtable_class': vtable_class,
    'vtable_symbol': vtable_symbol,
    'vtable_va': hex(vtable_va),
    'vtable_rva': hex(vtable_rva),
    'vtable_size': hex(vtable_size),
    'vtable_numvfunc': count,
    'vtable_entries': {i: hex(entry) for i, entry in enumerate(vtable_entries)}
}

yaml_path = os.path.join(dir_path, f"{vtable_class}_vtable.{platform}.yaml")
with open(yaml_path, 'w', encoding='utf-8') as f:
    yaml.dump(yaml_data, f, default_flow_style=False, sort_keys=False, allow_unicode=True)
print(f"Written to: {yaml_path}")
"""

Read the full file on GitHub · 174 lines

Changes

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.

  1. 3d ago Changed · +4 lines ba7c10a027df
  2. 9d ago First seen · 170 lines · 42 tokens per session scan A 5edd9e856882

Subscribe to this mod's changes

write-vtable-as-yaml is a skill published in the GitHub repository HLND2T/CS2_VibeSignatures (65 stars, last pushed today), licensed MIT. It adds 42 tokens to every session and 1,728 once invoked, about $0.0002 per session on Opus 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.

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