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 agentmods add skills/marcosd4h/deepextractruntime/com-interface-reconstructionnpx skills add marcosd4h/DeepExtractRuntime --skill com-interface-reconstructiongit clone --depth 1 https://github.com/marcosd4h/DeepExtractRuntimeWrote 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/marcosd4h/deepextractruntime/com-interface-reconstruction)<a href="https://agentmods.dev/skills/marcosd4h/deepextractruntime/com-interface-reconstruction"><img src="https://agentmods.dev/badge/skills/marcosd4h/deepextractruntime/com-interface-reconstruction.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00100 | $0.03061 |
| Opus 5 | $0.00050 | $0.01530 |
| Sonnet 5 | $0.00020 | $0.00612 |
| Haiku 4.5 | $0.00010 | $0.00306 |
Grade A, and why
com-interface-reconstruction 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 4d 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 — 306 lines — stays where its author put it; the contents beside it link to each section on GitHub.
COM / WRL Interface Reconstruction
Purpose
Reconstruct complete COM interface and WRL class definitions from DeepExtractIDA analysis databases. Windows binaries are heavily COM-based; this skill extracts structured COM metadata from:
- VTable slot analysis -- map vtable layouts to COM interface method tables
- QueryInterface/AddRef/Release patterns -- identify IUnknown implementations
- Mangled name decoding -- extract full C++ type info from MSVC mangled names
- WRL template instantiation decoding -- parse
Microsoft::WRL::*template parameters to recover interface lists, RuntimeClassFlags, and class hierarchies - Decompiled code pattern matching -- find QI dispatch tables, CLSID registrations, and class factory patterns
Output is structured COM metadata: interfaces with method slots, class-to-interface maps, WRL template breakdowns, and IDL-like descriptions.
This is NOT security analysis. The goal is faithful COM structure reconstruction.
Data Sources
SQLite Databases (primary)
Individual analysis DBs in extracted_dbs/ provide per-function data:
| Field | COM Relevance |
|---|---|
mangled_name |
Full C++ type info: WRL templates, interface names, class names |
vtable_contexts |
Reconstructed class skeletons with virtual method slots |
function_name / function_signature |
Demangled names showing COM patterns |
outbound_xrefs |
VTable call info (is_vtable_call, vtable_info), CoCreateInstance calls |
simple_outbound_xrefs |
Simplified callee info for API usage detection |
decompiled_code |
QI dispatch logic, GUID comparisons, class factory implementations |
string_literals |
GUID strings, interface name strings |
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 4d ago First seen · 306 lines · 100 tokens per session scan A b4134b3ca61f
com-interface-reconstruction is a skill published in the GitHub repository marcosd4h/DeepExtractRuntime (19 stars, last pushed 4mo ago), licensed MIT. It adds 100 tokens to every session and 3,061 once invoked, about $0.0005 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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