AuC is a Python framework for running a single AI agent with an asynchronous, pluggable reasoning loop, language-model adapters, permission levels, and observable events. It is used to build coding and conversational agents with tools, security checks, web interfaces, background jobs, evaluations, and isolated execution. The catalogue entries are skills for extending its agent workflow.
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 ufy2024/AuC --skill gateguardgit clone --depth 1 https://github.com/ufy2024/AuCWrote 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/ufy2024/auc/gateguard)<a href="https://agentmods.dev/skills/ufy2024/auc/gateguard"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/gateguard/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/ufy2024/auc/gateguard"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/gateguard.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 | $0.00058 | $0.01337 |
| Opus 5 | $0.00029 | $0.00668 |
| Sonnet 5 | $0.00012 | $0.00267 |
| Haiku 4.5 | $0.00006 | $0.00134 |
Grade C, and why
gateguard scanned grade C with 1 finding 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
Triggers on: `rm -rf`, `git reset --hard`, `git push --force`, `drop table`, etc. Copies of this mod
1 near-identical copy found in the catalogue:
- gateguard — 95% identical, 33 lines differ
How it starts
The opening of the file, as written. The whole thing — 155 lines — stays where its author put it; the contents beside it link to each section on GitHub.
GateGuard — Fact-Forcing Pre-Action Gate
A PreToolUse hook that forces Claude to investigate before editing. Instead of self-evaluation ("are you sure?"), it demands concrete facts. The act of investigation creates awareness that self-evaluation never did.
When to Activate
- Working on any codebase where file edits affect multiple modules
- Projects with data files that have specific schemas or date formats
- Teams where AI-generated code must match existing patterns
- Any workflow where Claude tends to guess instead of investigating
Core Concept
LLM self-evaluation doesn't work. Ask "did you violate any policies?" and the answer is always "no." This is verified experimentally.
But asking "list every file that imports this module" forces the LLM to run Grep and Read. The investigation itself creates context that changes the output.
Three-stage gate:
1. DENY — block the first Edit/Write/Bash attempt
2. FORCE — tell the model exactly which facts to gather
3. ALLOW — permit retry after facts are presented
No competitor does all three. Most stop at deny.
Evidence
Two independent A/B tests, identical agents, same task:
| Task | Gated | Ungated | Gap |
|---|---|---|---|
| Analytics module | 8.0/10 | 6.5/10 | +1.5 |
| Webhook validator | 10.0/10 | 7.0/10 | +3.0 |
| Average | 9.0 | 6.75 | +2.25 |
Both agents produce code that runs and passes tests. The difference is design depth.
Gate Types
Edit / MultiEdit Gate (first edit per file)
MultiEdit is handled identically — each file in the batch is gated individually.
Before editing {file_path}, present these facts:
1. List ALL files that import/require this file (search the tree — Glob/Grep, or find/grep via Bash)
2. List the public functions/classes affected by this change
3. If this file reads/writes data files, show field names, structure,
and date format (use redacted or synthetic values, not raw production data)
4. Quote the user's current instruction verbatim
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 · 155 lines · 58 tokens per session scan C 4771557cb2bf
gateguard is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 58 tokens to every session and 1,337 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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