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 competitive-platform-analysisgit 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/competitive-platform-analysis)<a href="https://agentmods.dev/skills/ufy2024/auc/competitive-platform-analysis"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/competitive-platform-analysis/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/competitive-platform-analysis"><img src="https://agentmods.dev/badge/skills/ufy2024/auc/competitive-platform-analysis.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 | $0.00065 | $0.02799 |
| Opus 5 | $0.00032 | $0.01399 |
| Sonnet 5 | $0.00013 | $0.00560 |
| Haiku 4.5 | $0.00006 | $0.00280 |
Grade A, and why
competitive-platform-analysis 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.
This is a copy
94% identical to competitive-platform-analysis — 32 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 — 233 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Competitive Platform Analysis
Use this skill to decide who to benchmark and where to find them before any scoring begins. A competitive analysis is only as good as its frame: the wrong set makes the client look either unbeatable or doomed. The goal is a defensible, decision-relevant set — not an exhaustive census.
When to Activate
- About to start a competitive benchmarking project and need to define the competitor set first.
- Unsure which companies belong in Direct / Adjacent / Aspirational tiers.
- Need a defensible, pruned scope for a market landscape report.
- Has a positioning brief and wants to identify who contests that position.
- First step before running benchmark-methodology.
Client positioning brief (establish first)
Before scoping the set, establish the client's positioning brief. If you don't already have it, run a short brand-discovery interview to elicit it — do not invent one and do not scope the set blind. The brief supplies:
- Identity / aesthetic register — what kind of studio or company this is and how it presents itself.
- Offer — what services or products it delivers.
- Target clients — who it sells to.
- Differentiator — the moat or positioning argument the client believes in.
- Scoping consequence — the implication for how to weight competitors (e.g., prioritize by distinctiveness vs. capability overlap vs. price).
- Strategic tension — the paired axes that define the client's white-space (e.g., memorability × hireability).
Do not proceed without the positioning brief. A competitor list scoped without the client's lens is noise, not intelligence. The scoping consequence in particular determines which competitors are strong rivals (those that contest the client's moat) vs. merely overlapping on service menu.
Selection criteria
For each candidate, capture these axes — they decide both inclusion and tier:
- Size / model — solo, micro-studio (2–8), boutique (sub-30), mid-size agency. Match the client's own band; same-band studios are the realistic head-to-head set.
- Niche / specialization — how closely the candidate's focus overlaps with the client's offer. Tighter overlap = more direct.
- Geography / market — EU vs US vs global-remote; language; time-zone reach. Note whether they win the same clients the client targets.
- Pricing & engagement model — productized sprints, retainer, project, day-rate; transparent vs "contact us". Signals positioning maturity.
- Portfolio style — generic vs. opinionated/editorial vs. contrarian. Closer to the client's aesthetic register = more they contest the client's distinctiveness.
- Technical depth / craft maturity — relevant if the client's credibility story includes public process work, open tooling, or documented systems.
- Brand strength — does the studio have an ownable verbal/visual identity, or is it interchangeable? Weight this per the client's scoping consequence.
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 · 233 lines · 65 tokens per session scan A edaa5a34b1f5
competitive-platform-analysis is a skill published in the GitHub repository ufy2024/AuC (1,090 stars, last pushed 1mo ago), licensed MIT. It adds 65 tokens to every session and 2,799 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to competitive-platform-analysis, differing in 32 lines, and is treated as a copy.
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