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 analyzing-rich-header-and-compiler-artifactsgit 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/analyzing-rich-header-and-compiler-artifacts)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/analyzing-rich-header-and-compiler-artifacts"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/analyzing-rich-header-and-compiler-artifacts/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/analyzing-rich-header-and-compiler-artifacts"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/analyzing-rich-header-and-compiler-artifacts.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 | $0.00065 | $0.00649 |
| Opus 5 | $0.00032 | $0.00324 |
| Sonnet 5 | $0.00013 | $0.00130 |
| Haiku 4.5 | $0.00006 | $0.00065 |
Grade A, and why
analyzing-rich-header-and-compiler-artifacts 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 12d 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
Analyzing Rich Header and Compiler Artifacts
When to Use
- You have a Windows PE and want to fingerprint its build toolchain (compiler/linker product IDs and build numbers) from the Rich header.
- You are clustering samples by toolchain or detecting Rich-header tampering/forgery.
Do not use the Rich header as definitive attribution — it can be copied or stripped. This skill reads the PE statically and executes nothing.
Prerequisites
- The PE sample (read inertly).
Safety & Handling
- Read bytes statically; treat the sample as malicious data.
Workflow
Step 1: Parse and decode the Rich header
python scripts/analyst.py rich sample.exe
Locates the Rich marker, recovers the XOR key (the DWORD after Rich), decodes the DanS-
prefixed entries, and lists (product_id, build_id, use_count) tuples.
Step 2: Fingerprint the toolchain
Map product IDs to compiler/linker products and build numbers to identify the Visual Studio version(s) used.
Step 3: Compute a clustering hash
Hash the decoded Rich entries to produce a toolchain fingerprint for grouping related samples.
Step 4: Check for inconsistencies
Compare the Rich-derived linker version against the PE optional-header linker version; mismatches suggest tampering or a copied header.
Validation
- The XOR key correctly decodes the
DanSsignature at the start of the block. - Decoded entries have plausible product IDs and use counts.
- The toolchain fingerprint is reproducible across identical builds.
Pitfalls
- Samples with no Rich header (non-MSVC toolchains, stripped headers).
- Forged Rich headers copied from a benign binary.
- Confusing the Rich checksum/key handling and misdecoding entries.
References
- See
references/api-reference.mdfor the parser. - PE format documentation (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.
- 12d ago First seen · 90 lines · 65 tokens per session scan A abe420462d65
analyzing-rich-header-and-compiler-artifacts is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 65 tokens to every session and 649 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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