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 identifying-file-types-and-formatsgit 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/identifying-file-types-and-formats)<a href="https://agentmods.dev/skills/meltedinhex/analyst-ai-pack/identifying-file-types-and-formats"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/identifying-file-types-and-formats/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/identifying-file-types-and-formats"><img src="https://agentmods.dev/badge/skills/meltedinhex/analyst-ai-pack/identifying-file-types-and-formats.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 | $0.00069 | $0.00717 |
| Opus 5 | $0.00034 | $0.00358 |
| Sonnet 5 | $0.00014 | $0.00143 |
| Haiku 4.5 | $0.00007 | $0.00072 |
Grade A, and why
identifying-file-types-and-formats 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 7d 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 — 90 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Identifying File Types and Formats
When to Use
- You receive an unknown sample and must determine what it actually is before choosing tools.
- You suspect masquerading — a
.pdfor.jpgthat is really an executable or script. - You need to detect container formats (ZIP/OLE/ISO) that hide a payload.
Do not use the file extension or the OS-reported type as truth — adversaries rename executables and embed payloads; always confirm by content.
Prerequisites
file/libmagic or an equivalent magic-byte database; the sample handled inertly in the lab.
Safety & Handling
- Never open the sample in its associated application during identification; read raw bytes only.
- Keep the disguised extension in mind — a double extension or RTLO trick can mislead the eye.
Workflow
Step 1: Read the magic bytes
Inspect the leading bytes and known offset signatures (e.g., MZ, \x7fELF, %PDF, PK\x03\x04,
OLE D0 CF 11 E0).
python scripts/analyst.py identify sample.dat
Step 2: Confirm structure
For container formats, confirm internal structure (ZIP central directory, OLE storage, ISO
CD001 at 0x8001) rather than trusting the header alone.
Step 3: Compare against the claimed extension
Flag mismatches: a .jpg whose content is MZ, or a document that is actually a script. These
are strong masquerading indicators.
Step 4: Route to the right analysis
Use the confirmed type to pick the correct workflow (PE static analysis, document analysis, archive extraction).
Validation
- The detected type is confirmed by both magic bytes and structural checks, not magic alone.
- Extension/content mismatches are explicitly reported.
- The result correctly routes the sample to the appropriate analysis skill.
Pitfalls
- Trusting the first 2 bytes only; some formats need offset or structural confirmation.
- Missing polyglot files that are valid as two formats at once.
- Overlooking nested containers (archive inside archive) that hide the real payload.
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.
- 7d ago First seen · 90 lines · 69 tokens per session scan A 47230f329bd6
identifying-file-types-and-formats is a skill published in the GitHub repository meltedinhex/analyst-ai-pack (22 stars, last pushed 2mo ago), licensed Apache-2.0. It adds 69 tokens to every session and 717 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 2026-09-03.
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