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.
git clone --depth 1 https://github.com/kunalsuri/ai-fication-kitWrote 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/commands/kunalsuri/ai-fication-kit/adversarial-audit)<a href="https://agentmods.dev/commands/kunalsuri/ai-fication-kit/adversarial-audit"><img src="https://agentmods.dev/badge/commands/kunalsuri/ai-fication-kit/adversarial-audit/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/commands/kunalsuri/ai-fication-kit/adversarial-audit"><img src="https://agentmods.dev/badge/commands/kunalsuri/ai-fication-kit/adversarial-audit.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 | $0.00049 | $0.01095 |
| Opus 5.5 | $0.00020 | $0.00438 |
| Sonnet 5.5 | $0.00010 | $0.00219 |
| Haiku 4.5 | $0.00005 | $0.00110 |
Grade A, and why
adversarial-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 28d 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 — 86 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Run a deep, adversarial audit of the current codebase. This is not the
mechanical verify/drift check — those confirm paths exist. This hunts for
defects those checks categorically cannot catch: places where the code's
actual behavior no longer matches what the code, comments, or docs say it
does, or where a change elsewhere in the repo silently broke an assumption
made here.
Read-only. Do not edit any file other than the report this command writes. Full-repo scope every run — do not sample or skip areas because they seem stable; staleness hides exactly where nobody looked recently.
What to hunt for
- Stale cross-references — comments, docstrings, or user-facing strings
describing behavior a later change invalidated. Search for "never",
"always", "not yet available", "no writes unless X", "once available",
TODO, and version/feature gates — then verify the referenced behavior against the current code, not what was true when the comment was written. - Unquoted/unescaped interpolation — any generated shell command, CLI suggestion, file path, or subprocess argument built by string concatenation or a template literal without quoting/escaping. Check every subprocess spawn/exec call and every "here's the command to run" string for inputs that could contain spaces or shell metacharacters.
- Platform-specific gaps — subprocess calls or path handling that assume
POSIX (missing a shell flag for
.cmd-shimmed binaries on Windows, hardcoded path separators, case-sensitivity assumptions). Flag anything that has never actually been exercised cross-platform. - Ownership conflicts on generated files — any file written by more than one code path (scaffolded once, then continuously regenerated by a live process). Check whether "protect user edits" / backup / diffing logic correctly distinguishes "changed because it's supposed to" from "changed because a human edited it."
- Mechanical vs. semantic validation gaps — places where an automated check only confirms a path or reference exists, not that the prose describing it is still accurate. List every place documentation makes a factual claim about code behavior and check it against the current implementation.
- Cross-module consistency after incremental changes — for every function or module that references another component's state, existence, or capabilities, confirm that reference is re-validated, not assumed from when it was first written.
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.
- 28d ago First seen · 86 lines · 49 tokens per session scan A f8638eff98f0
adversarial-audit is a command published in the GitHub repository kunalsuri/ai-fication-kit (3 stars, last pushed today), licensed Apache-2.0. It adds 49 tokens to every session and 1,095 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-18.
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