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/stefanthecode/dotnet-ai-toolkit/adonet-data-access-auditornpx skills add StefanTheCode/dotnet-ai-toolkit --skill adonet-data-access-auditorgit clone --depth 1 https://github.com/StefanTheCode/dotnet-ai-toolkitWrote 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/stefanthecode/dotnet-ai-toolkit/adonet-data-access-auditor)<a href="https://agentmods.dev/skills/stefanthecode/dotnet-ai-toolkit/adonet-data-access-auditor"><img src="https://agentmods.dev/badge/skills/stefanthecode/dotnet-ai-toolkit/adonet-data-access-auditor.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 | $0.00144 | $0.02263 |
| Opus 5 | $0.00072 | $0.01131 |
| Sonnet 5 | $0.00029 | $0.00453 |
| Haiku 4.5 | $0.00014 | $0.00226 |
Grade A, and why
adonet-data-access-auditor 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 5d 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 — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ADO.NET Data Access Auditor
Audit classic ADO.NET code for the three things that go wrong in 20-year-old data layers -- SQL injection, leaked connections/commands/readers, and wasteful repeated reads -- then return the rewritten code with a one-line explanation per fix. This is for the old stack (System.Data.SqlClient / Microsoft.Data.SqlClient, SqlDataReader, DataSet/DataTable), not EF Core.
When this runs
The user has hand-written ADO.NET (a DAL, a repository, a Helper class full of SqlCommands) and wants it made safe, leak-free, and faster -- or reviewed before a migration. They may paste code or point at a file. If nothing is provided, ask for the data-access method(s) and how the connection string is obtained.
Input — point it at your code
You don't need pasted snippets. Work from whatever target the user gives:
- A single file —
path/to/OrderRepository.cs - A folder — a
Data/orDAL/directory - A whole project or solution — a
.csproj/.slnor the repo root - A GitHub URL — clone first:
git clone --depth 1 <url> /tmp/repo && cd /tmp/repo
Find the ADO.NET yourself with Glob/Grep/Bash instead of asking for a paste:
grep -rl "SqlCommand\|SqlConnection\|SqlDataReader\|SqlDataAdapter" --include=*.cs <target> | grep -vi "/obj/\|/bin/"
grep -rn "ExecuteReader\|ExecuteNonQuery\|\" + \|GetOrdinal" --include=*.cs <target>
On a large data layer, prioritize the worst offenders (string-built SQL, undisposed connections) and tell the user which files you scanned.
Workflow
- Read the code and the data flow. Identify every
SqlConnection,SqlCommand,SqlDataReader,DataAdapter,DataSet, and where user input enters the SQL. - Run the checklist below against every command.
- Rewrite the problematic methods. Preserve behavior unless you find a bug (call bugs out separately).
- Explain each change in one line -- what was wrong, why it matters, what the fix does.
- Flag what you cannot verify (e.g. column ordinals depend on the actual proc; mark "verify").
What ships with it
1 file 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.
- 5d ago First seen · 136 lines · 144 tokens per session scan A ec11339b6483
adonet-data-access-auditor is a skill published in the GitHub repository StefanTheCode/dotnet-ai-toolkit (19 stars, last pushed 26d ago), licensed MIT. It adds 144 tokens to every session and 2,263 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 2026-08-30.
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