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-materialsgit 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-materials)<a href="https://agentmods.dev/skills/ufy2024/auc/investor-materials"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/investor-materials/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-materials"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/investor-materials.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 | $0.00061 | $0.00675 |
| Opus 5 | $0.00030 | $0.00338 |
| Sonnet 5 | $0.00012 | $0.00135 |
| Haiku 4.5 | $0.00006 | $0.00068 |
Grade A, and why
investor-materials 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-materials — 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 — 119 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Investor Materials
Build investor-facing materials that are consistent, credible, and easy to defend.
When to Activate
- creating or revising a pitch deck
- writing an investor memo or one-pager
- building a financial model, milestone plan, or use-of-funds table
- answering accelerator or incubator application questions
- aligning multiple fundraising docs around one source of truth
Golden Rule
All investor materials must agree with each other.
Create or confirm a single source of truth before writing:
- traction metrics
- pricing and revenue assumptions
- raise size and instrument
- use of funds
- team bios and titles
- milestones and timelines
If conflicting numbers appear, stop and resolve them before drafting.
Core Workflow
- inventory the canonical facts
- identify missing assumptions
- choose the asset type
- draft the asset with explicit logic
- cross-check every number against the source of truth
Asset Guidance
Pitch Deck
Recommended flow:
- company + wedge
- problem
- solution
- product / demo
- market
- business model
- traction
- team
- competition / differentiation
- ask
- use of funds / milestones
- appendix
If the user wants a web-native deck, pair this skill with frontend-slides.
One-Pager / Memo
- state what the company does in one clean sentence
- show why now
- include traction and proof points early
- make the ask precise
- keep claims easy to verify
Financial Model
Include:
- explicit assumptions
- bear / base / bull cases when useful
- clean layer-by-layer revenue logic
- milestone-linked spending
- sensitivity analysis where the decision hinges on assumptions
Accelerator Applications
- answer the exact question asked
- prioritize traction, insight, and team advantage
- avoid puffery
- keep internal metrics consistent with the deck and model
Red Flags to Avoid
- unverifiable claims
- fuzzy market sizing without assumptions
- inconsistent team roles or titles
- revenue math that does not sum cleanly
- inflated certainty where assumptions are fragile
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 · 119 lines · 61 tokens per session scan A 6091e7e9243c
investor-materials is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 61 tokens to every session and 675 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-materials, differing in 27 lines, and is treated as a copy.
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