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 investor-outreachgit 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/investor-outreach)<a href="https://agentmods.dev/skills/ufy2024/auc/investor-outreach"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/investor-outreach/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/investor-outreach"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/investor-outreach.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 | $0.00054 | $0.00692 |
| Opus 5 | $0.00027 | $0.00346 |
| Sonnet 5 | $0.00011 | $0.00138 |
| Haiku 4.5 | $0.00005 | $0.00069 |
Grade A, and why
investor-outreach 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
95% identical to investor-outreach — 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 — 114 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investor Outreach
Write investor communication that is short, concrete, and easy to act on.
When to Activate
- writing a cold email to an investor
- drafting a warm intro request
- sending follow-ups after a meeting or no response
- writing investor updates during a process
- tailoring outreach based on fund thesis or partner fit
Core Rules
- Personalize every outbound message.
- Keep the ask low-friction.
- Use proof instead of adjectives.
- Stay concise.
- Never send copy that could go to any investor.
Voice Handling
If the user's voice matters, run brand-voice first and reuse its VOICE PROFILE.
This skill should keep the investor-specific structure and ask discipline, not recreate its own parallel voice system.
Hard Bans
Delete and rewrite any of these:
- "I'd love to connect"
- "excited to share"
- generic thesis praise without a real tie-in
- vague founder adjectives
- begging language
- soft closing questions when a direct ask is clearer
Cold Email Structure
- subject line: short and specific
- opener: why this investor specifically
- pitch: what the company does, why now, and what proof matters
- ask: one concrete next step
- sign-off: name, role, and one credibility anchor if needed
Personalization Sources
Reference one or more of:
- relevant portfolio companies
- a public thesis, talk, post, or article
- a mutual connection
- a clear market or product fit with the investor's focus
If that context is missing, state that the draft still needs personalization instead of pretending it is finished.
Follow-Up Cadence
Default:
- day 0: initial outbound
- day 4 or 5: short follow-up with one new data point
- day 10 to 12: final follow-up with a clean close
Do not keep nudging after that unless the user wants a longer sequence.
Warm Intro Requests
Make life easy for the connector:
- explain why the intro is a fit
- include a forwardable blurb
- keep the forwardable blurb under 100 words
Post-Meeting Updates
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 · 114 lines · 54 tokens per session scan A 79e4a3bdd4f8
investor-outreach is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 54 tokens to every session and 692 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 95% identical to investor-outreach, differing in 27 lines, and is treated as a copy.
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