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 inherit-legacy-stylegit 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/inherit-legacy-style)<a href="https://agentmods.dev/skills/ufy2024/auc/inherit-legacy-style"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/inherit-legacy-style/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/inherit-legacy-style"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/inherit-legacy-style.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 4 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Anti-Refusal · line 151 Skill instructs the agent to omit warnings, disclaimers, or ethical commentary. Stripping safety caveats hides risk from the user and is a common jailbreak preamble.Fix: Remove instructions that suppress warnings, disclaimers, or ethical commentary. Let the agent surface safety-relevant caveats to the user.
- medium Agent Snooping · line 25 Skill enumerates or reads other installed skills. Access to other skills' SKILL.md files or the skills directory reveals prompt instructions, capabilities, and secrets that should be invisible to peer skills.Fix: Remove all code or instructions that list or read other skills' files or directories. Skills should operate independently; cross-skill access is a privilege escalation.
- medium Excessive Agency · line 63 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
- medium Excessive Agency · line 150 Skill enables autonomous high-impact decisions without human-in-the-loop verification. Critical operations (destructive commands, financial transactions, data deletion) should require explicit user confirmation.Fix: Add human-in-the-loop confirmation for destructive, irreversible, or high-impact operations. Never auto-execute commands that modify files, send data, or alter system state.
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 | $0.00105 | $0.02088 |
| Opus 5 | $0.00053 | $0.01044 |
| Sonnet 5 | $0.00021 | $0.00418 |
| Haiku 4.5 | $0.00011 | $0.00209 |
Grade A, and why
inherit-legacy-style 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 8d 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.
Copies of this mod
2 near-identical copies found in the catalogue:
- inherit-legacy-style — 94% identical, 33 lines differ
- inherit-legacy-style — 94% identical, 33 lines differ
How it starts
The opening of the file, as written. The whole thing — 181 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Inherit Legacy Style
Prevents AI code style drift in legacy projects by scanning the codebase for implicit conventions across 4 meta-architecture dimensions, resolving conflicts with the user one at a time, and crystallizing the consensus into an enforceable .ai-style-rules.md. Fully language- and framework-agnostic.
When to Activate
- User types
/inherit-legacy-style - User mentions onboarding AI onto a hand-written legacy project
- User is worried about AI-generated code "drifting" from existing project conventions
- User wants to extract and codify their project's implicit coding rules
When to Use
Use this skill when you need to preserve legacy project style and prevent AI-generated style drift. See When to Activate above for trigger conditions.
Prerequisites
- Git (recommended; non-Git projects fall back to file timestamps for incremental mode)
- Read/Write access to the project root (generates
.ai-style-rules.mdand optionallyCLAUDE.md)
Workflow
Step 0 — Auto-Detect Mode
Silently check for .ai-style-rules.md at the project root:
| File exists? | Mode |
|---|---|
| No | Branch A — First-time Full-Scan |
| Yes | Branch B — Incremental Sniff |
Announce the mode in one line and proceed — never ask the user to pick.
Branch A — First-time Full-Scan
1. Measure scale, pick a scanning tier
git ls-files | grep -cE '\.(js|ts|jsx|tsx|vue|py|go|rs|java|kt|rb|php|cs|swift|c|cpp|h)$'
| Tier | Source files | Strategy |
|---|---|---|
| Small | ≲ 50 | Full close-read every source |
| Medium | 50–500 | Infra layer = full read; business layer = sample 2–3 per dimension |
| Large | ≳ 500 | Strict sampling + budget cap; --stat summary first, then targeted reads |
2. Scan along 4 dimensions
- File Anatomy — in-file declaration order (imports → types → main logic → helpers → export)
- State & Control Flow — naming conventions for async state, pagination, flags
- Infrastructure — where cross-cutting utils live (interceptors, formatters, middleware)
- Error Handling — try/catch vs global interceptor vs Result return; null-check habits
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.
- 8d ago First seen · 181 lines · 105 tokens per session scan A 5bbf07219b42
inherit-legacy-style is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 105 tokens to every session and 2,088 once invoked, about $0.0005 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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