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 jinyimeng01/net-code-audit-skill-master --skill dotnet-deserialization-auditgit clone --depth 1 https://github.com/jinyimeng01/net-code-audit-skill-masterWrote 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/jinyimeng01/net-code-audit-skill-master/dotnet-deserialization-audit)<a href="https://agentmods.dev/skills/jinyimeng01/net-code-audit-skill-master/dotnet-deserialization-audit"><img src="https://agentmods.dev/badge/skills/jinyimeng01/net-code-audit-skill-master/dotnet-deserialization-audit.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 | $0.00132 | $0.01219 |
| Opus 5 | $0.00066 | $0.00609 |
| Sonnet 5 | $0.00026 | $0.00244 |
| Haiku 4.5 | $0.00013 | $0.00122 |
Grade A, and why
dotnet-deserialization-audit 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.
The source is not reproduced here
Licensed MulanPSL-2.0
The repository is licensed MulanPSL-2.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What ships with it
17 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.
- agents/openai.yaml 792 B
- references/DESERIALIZATION_MATRIX.md 2.9 KB
- references/FORMATTER_PLAYBOOK.md 7.7 KB
- references/RAW_REFERENCE_INDEX.md 1.3 KB
- references/raw/deserialization/lesson-01-xmlserializer.md 19 KB
- references/raw/deserialization/lesson-02-json-net.md 22 KB
- references/raw/deserialization/lesson-03-fastjson.md 14 KB
- references/raw/deserialization/lesson-04-javascriptserializer.md 14 KB
- references/raw/deserialization/lesson-05-dotnet-remoting.md 24 KB
- references/raw/deserialization/lesson-06-datacontractserializer.md 19 KB
- references/raw/deserialization/lesson-07-netdatacontractserializer.md 20 KB
- references/raw/deserialization/lesson-08-soapformatter.md 22 KB
- references/raw/deserialization/lesson-09-binaryformatter.md 9.9 KB
- references/raw/deserialization/lesson-10-objectstateformatter.md 15 KB
- references/raw/deserialization/lesson-11-losformatter.md 11 KB
- references/TYPE_CONTROL_AND_GADGETS.md 1.8 KB
- references/VIEWSTATE_MACHINEKEY.md 1.9 KB
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 · 59 lines · 132 tokens per session scan A befdaa51567a
dotnet-deserialization-audit is a skill published in the GitHub repository jinyimeng01/net-code-audit-skill-master (5 stars, last pushed 4mo ago), licensed MulanPSL-2.0. It adds 132 tokens to every session and 1,219 once invoked, about $0.0007 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 2026-08-31.
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