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 agentmods add skills/ufy2024/auc/click-path-auditnpx skills add ufy2024/AuC --skill click-path-auditgit 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/click-path-audit)<a href="https://agentmods.dev/skills/ufy2024/auc/click-path-audit"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/click-path-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 | $0.00071 | $0.02046 |
| Opus 5 | $0.00036 | $0.01023 |
| Sonnet 5 | $0.00014 | $0.00409 |
| Haiku 4.5 | $0.00007 | $0.00205 |
Grade A, and why
click-path-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 yesterday.
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.
Copies of this mod
6 near-identical copies found in the catalogue:
- click-path-audit — 94% identical, 28 lines differ
- click-path-audit — 94% identical, 28 lines differ
- click-path-audit — 94% identical, 28 lines differ
- click-path-audit — 92% identical, 27 lines differ
- click-path-audit — 92% identical, 42 lines differ
- click-path-audit — 92% identical, 27 lines differ
How it starts
The opening of the file, as written. The whole thing — 266 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/click-path-audit — Behavioural Flow Audit
Find bugs that static code reading misses: state interaction side effects, race conditions between sequential calls, and handlers that silently undo each other.
The Problem This Solves
Traditional debugging checks:
- Does the function exist? (missing wiring)
- Does it crash? (runtime errors)
- Does it return the right type? (data flow)
But it does NOT check:
- Does the final UI state match what the button label promises?
- Does function B silently undo what function A just did?
- Does shared state (Zustand/Redux/context) have side effects that cancel the intended action?
Real example: A "New Email" button called setComposeMode(true) then selectThread(null). Both worked individually. But selectThread had a side effect resetting composeMode: false. The button did nothing. 54 bugs were found by systematic debugging — this one was missed.
How It Works
For EVERY interactive touchpoint in the target area:
1. IDENTIFY the handler (onClick, onSubmit, onChange, etc.)
2. TRACE every function call in the handler, IN ORDER
3. For EACH function call:
a. What state does it READ?
b. What state does it WRITE?
c. Does it have SIDE EFFECTS on shared state?
d. Does it reset/clear any state as a side effect?
4. CHECK: Does any later call UNDO a state change from an earlier call?
5. CHECK: Is the FINAL state what the user expects from the button label?
6. CHECK: Are there race conditions (async calls that resolve in wrong order)?
Execution Steps
Step 1: Map State Stores
Before auditing any touchpoint, build a side-effect map of every state store action:
For each Zustand store / React context in scope:
For each action/setter:
- What fields does it set?
- Does it RESET other fields as a side effect?
- Document: actionName → {sets: [...], resets: [...]}
This is the critical reference. The "New Email" bug was invisible without knowing that selectThread resets composeMode.
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.
- yesterday First seen · 266 lines · 71 tokens per session scan A 5e79007ff9bb
click-path-audit is a skill published in the GitHub repository ufy2024/AuC (1,091 stars, last pushed 1mo ago), licensed MIT. It adds 71 tokens to every session and 2,046 once invoked, about $0.0004 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 2026-09-03.
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