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 meltedinhex/analyst-ai-pack --skill reverse-engineering-nim-and-other-exotic-binariesgit clone --depth 1 https://github.com/meltedinhex/analyst-ai-packWrote 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/meltedinhex/analyst-ai-pack/reverse-engineering-nim-and-other-exotic-binaries)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/reverse-engineering-nim-and-other-exotic-binaries"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/reverse-engineering-nim-and-other-exotic-binaries/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/meltedinhex/analyst-ai-pack/reverse-engineering-nim-and-other-exotic-binaries"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/reverse-engineering-nim-and-other-exotic-binaries.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00080 | $0.00722 |
| Opus 5 | $0.00040 | $0.00361 |
| Sonnet 5 | $0.00016 | $0.00144 |
| Haiku 4.5 | $0.00008 | $0.00072 |
Grade A, and why
reverse-engineering-nim-and-other-exotic-binaries 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 9d 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.
What it actually says
Reverse Engineering Nim and Other Exotic Binaries
When to Use
- You have a compiled binary that is not C/C++/Go/Rust/.NET and need to identify its source language (Nim, Crystal, V, Zig, D) to orient analysis.
- Symbol/runtime patterns are unfamiliar and you want language-specific landmarks.
Do not use this for already-supported languages (Go/Rust have dedicated skills). This skill reads the binary statically and executes nothing.
Prerequisites
- The binary (read inertly).
Safety & Handling
- Read bytes statically; treat strings as untrusted.
Workflow
Step 1: Detect the source language
python scripts/analyst.py detect sample.bin
Scans for language runtime signatures: Nim (@m..nim, nimrtl, fatal.nim, stack trace,
@ /nim), Crystal (Crystal::, crystal-lang), V (vlib/, _vinit), Zig (zig, panic: ,
std.builtin), and D (_Dmain, core.runtime, TypeInfo_).
Step 2: Locate runtime landmarks
Use the detected language's panic/exception and module strings to find main/init and error paths.
Step 3: Handle name mangling
Apply the language's mangling convention (e.g., Nim's proc__module_NNN) to recover readable
names.
Step 4: Proceed with analysis
With the language identified, analyze logic; many exotic-language samples wrap the same C2/loader behavior.
Validation
- Language detection is based on multiple corroborating runtime strings, not one weak hit.
- Identified landmarks (panic/init) are consistent with the language.
- Name demangling matches the language's documented scheme.
Pitfalls
- Statically linked C runtime strings causing misclassification — weight language-specific markers.
- Stripped binaries with few runtime strings.
- Stagers in exotic languages that quickly hand off to shellcode.
References
- See
references/api-reference.mdfor the detector. - Nim manual and ATT&CK T1027 references (linked in frontmatter).
What ships with it
3 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.
- 9d ago First seen · 91 lines · 80 tokens per session scan A f0d99a55db56
reverse-engineering-nim-and-other-exotic-binaries is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 80 tokens to every session and 722 once invoked, about $0.0004 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 2026-09-03.
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