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 crosspostgit 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/crosspost)<a href="https://agentmods.dev/skills/ufy2024/auc/crosspost"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/crosspost/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/crosspost"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/crosspost.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 | $0.00842 |
| Opus 5 | $0.00024 | $0.00421 |
| Sonnet 5 | $0.00010 | $0.00168 |
| Haiku 4.5 | $0.00005 | $0.00084 |
Grade A, and why
crosspost 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 9d 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.
This is a copy
89% identical to crosspost — 27 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 134 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Crosspost
Distribute content across platforms without turning it into the same fake post in four costumes.
When to Activate
- the user wants to publish the same underlying idea across multiple platforms
- a launch, update, release, or essay needs platform-specific versions
- the user says "crosspost", "post this everywhere", or "adapt this for X and LinkedIn"
Core Rules
- Do not publish identical copy across platforms.
- Preserve the author's voice across platforms.
- Adapt for constraints, not stereotypes.
- One post should still be about one thing.
- Do not invent a CTA, question, or moral if the source did not earn one.
Workflow
Step 1: Start with the Primary Version
Pick the strongest source version first:
- the original X post
- the original article
- the launch note
- the thread
- the memo or changelog
Use content-engine first if the source still needs voice shaping.
Step 2: Capture the Voice Fingerprint
Run brand-voice first if the source voice is not already captured in the current session.
Reuse the resulting VOICE PROFILE directly.
Do not build a second ad hoc voice checklist here unless the user explicitly wants a fresh override for this campaign.
Step 3: Adapt by Platform Constraint
X
- keep it compressed
- lead with the sharpest claim or artifact
- use a thread only when a single post would collapse the argument
- avoid hashtags and generic filler
- add only the context needed for people outside the niche
- do not turn it into a fake founder-reflection post
- do not add a closing question just because it is LinkedIn
- do not force a polished "professional tone" if the author is naturally sharper
Threads
- keep it readable and direct
- do not write fake hyper-casual creator copy
- do not paste the LinkedIn version and shorten it
Bluesky
- keep it concise
- preserve the author's cadence
- do not rely on hashtags or feed-gaming language
Posting Order
Default:
- post the strongest native version first
- adapt for the secondary platforms
- stagger timing only if the user wants sequencing help
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.
- 9d ago First seen · 134 lines · 49 tokens per session scan A f9fd9dc7820a
crosspost is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 49 tokens to every session and 842 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 89% identical to crosspost, differing in 27 lines, and is treated as a copy.
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