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/rpc-interface-analysisnpx skills add marcosd4h/DeepExtractRuntime --skill rpc-interface-analysisgit 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/rpc-interface-analysis)<a href="https://agentmods.dev/skills/marcosd4h/deepextractruntime/rpc-interface-analysis"><img src="https://agentmods.dev/badge/skills/marcosd4h/deepextractruntime/rpc-interface-analysis.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 | $0.00063 | $0.01530 |
| Opus 5 | $0.00032 | $0.00765 |
| Sonnet 5 | $0.00013 | $0.00306 |
| Haiku 4.5 | $0.00006 | $0.00153 |
Grade A, and why
rpc-interface-analysis 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 — 177 lines — stays where its author put it; the contents beside it link to each section on GitHub.
RPC Interface Analysis
Purpose
Query and analyze RPC (Remote Procedure Call) interfaces registered in Windows system binaries. Uses a pre-built index of NtApiDotNet-extracted RPC data that maps every binary to its interfaces, procedure names, endpoint protocols, service associations, and NDR complex types. Optionally enriches with C# client stub parameter signatures and procedure semantic classification.
When to Use
- Enumerate RPC interfaces in a module or system-wide
- Map the RPC attack surface ranked by risk tier
- Audit RPC handler security (missing impersonation, missing auth)
- Trace RPC handler data flow to dangerous sinks
- Analyze blast-radius of co-hosted interfaces in shared processes
- View typed parameter signatures from C# client stubs
- Build client-server topology graphs
When NOT to Use
- General function explanation -- use re-analyst
- COM interface reconstruction -- use com-interface-reconstruction
- Non-RPC attack surface mapping -- use map-attack-surface
Data Sources
- RPC index (
helpers/rpc_index.py): Singleton loaded fromconfig/assets/rpc_data/rpc_servers.json(binary-keyed; contains interface metadata, endpoints, file info, and procedure lists per binary). - C# client stubs (
config/assets/rpc_data/rpc_clients_26200_7840/*.cs): 414 auto-generated client stubs with typed procedure signatures. - Per-module analysis DB: Decompiled code for RPC handler functions.
Scripts
resolve_rpc_interface.py (Start Here)
List all RPC interfaces for a module with full metadata and optional stub
signatures. Use --workspace to discover which workspace modules implement
RPC interfaces.
python .claude/skills/rpc-interface-analysis/scripts/resolve_rpc_interface.py appinfo.dll
python .claude/skills/rpc-interface-analysis/scripts/resolve_rpc_interface.py appinfo.dll --json
python .claude/skills/rpc-interface-analysis/scripts/resolve_rpc_interface.py spoolsv.exe --with-stubs --json
python .claude/skills/rpc-interface-analysis/scripts/resolve_rpc_interface.py --workspace --json
What ships with it
8 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.
- reference.md 4.8 KB
- scripts/_common.py 1.1 KB runs code
- scripts/audit_rpc_security.py 12 KB runs code
- scripts/find_rpc_clients.py 2.9 KB runs code
- scripts/map_rpc_surface.py 4.1 KB runs code
- scripts/resolve_rpc_interface.py 4.7 KB runs code
- scripts/rpc_topology.py 7.9 KB runs code
- scripts/trace_rpc_chain.py 5.7 KB runs code
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 · 177 lines · 63 tokens per session scan A 402bd7482c70
rpc-interface-analysis is a skill published in the GitHub repository marcosd4h/DeepExtractRuntime (20 stars, last pushed 4mo ago), licensed MIT. It adds 63 tokens to every session and 1,530 once invoked, about $0.0003 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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