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/asaiuta/reverse-workbench-skill/competition-file-parser-chainnpx skills add Asaiuta/reverse-workbench-skill --skill competition-file-parser-chaingit clone --depth 1 https://github.com/Asaiuta/reverse-workbench-skillWrote 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/asaiuta/reverse-workbench-skill/competition-file-parser-chain)<a href="https://agentmods.dev/skills/asaiuta/reverse-workbench-skill/competition-file-parser-chain"><img src="https://agentmods.dev/badge/skills/asaiuta/reverse-workbench-skill/competition-file-parser-chain.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 5.1 | $0.00109 | $0.00613 |
| Opus 5 | $0.00055 | $0.00307 |
| Sonnet 5 | $0.00022 | $0.00123 |
| Haiku 4.5 | $0.00011 | $0.00061 |
Grade A, and why
competition-file-parser-chain 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 6d 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.
This is a copy
100% identical to competition-file-parser-chain — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 51 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competition File Parser Chain
Use this skill only as a downstream specialization after $ctf-sandbox-orchestrator is already active and has established sandbox assumptions, node ownership, and evidence priorities. If that has not happened yet, return to $ctf-sandbox-orchestrator first.
Use this skill when the hard part is following a file from ingress through every parser, extractor, converter, or deserializer boundary that matters.
Reply in Simplified Chinese unless the user explicitly requests English.
Quick Start
- Preserve the original upload and every derived artifact separately.
- Map the chain in order: ingress, temp storage, archive extraction, format conversion, parser call, deserialization, and final consumer.
- Record filenames, MIME guesses, extensions, temp paths, and parser choices before mutating anything.
- Separate client-visible validation from backend parser behavior.
- Reproduce the smallest file-processing chain that yields the decisive branch or artifact.
Workflow
1. Map File Ingress And Derivation
- Record request shape, multipart names, content type, filename, temp paths, upload staging, and storage keys.
- Note every derived artifact: extracted archive member, converted preview, generated thumbnail, temp document, or deserialized object.
- Keep original file and each derivative labeled separately.
2. Trace Parser And Conversion Boundaries
- Show which parser, converter, extractor, or deserializer runs at each step.
- Record parser-specific decisions driven by extension, MIME, magic bytes, schema, archive member names, or embedded metadata.
- Distinguish parsing success, preview success, conversion success, and business-logic acceptance.
3. Reduce To The Decisive File Chain
- Compress the result to the smallest sequence: upload -> derived artifact -> parser boundary -> resulting effect.
- State clearly whether the decisive weakness lives in archive handling, MIME inference, file conversion, path resolution, or deserialization.
- If the chain becomes mostly a generic async worker problem after enqueue, hand off to the tighter queue or worker skill.
What ships with it
2 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.
- 6d ago First seen · 51 lines · 109 tokens per session scan A ac09fa9241fd
competition-file-parser-chain is a skill published in the GitHub repository Asaiuta/reverse-workbench-skill (2 stars, last pushed 22d ago), licensed MIT. It adds 109 tokens to every session and 613 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to competition-file-parser-chain, differing in 0 lines, and is treated as a copy.
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