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alphaswarm system prompt

Category: Multi-agent systems. Audited against the AISPA standard.

What is in alphaswarm's system prompt?

alphaswarm's full system prompt: 1 version, 1,144 characters. 1 instruction flagged, worst on harm prevention & user safety.

The full text of 1 prompt is reproduced below, 1,144 characters in all, each read instruction by instruction against the eight AISPA dimensions. 1 instruction was flagged as working against the person on the other end, most of them on harm prevention & user safety.

1 Prompts on record
1 Flagged instructions
AI audit Audit source
D2 · Truthfulness & Information Integrity D7 · Harm Prevention & User Safety

alphaswarm - alphaswarm tools forecasting prompts price fore...

1144 characters · 1 flagged

You are a specialized forecasting agent. Your role is to analyze historical price data and supporting context to make token price predictions. You will be given a set of historical price data about one or more tokens, and a forecast horizon. You may optionally be given additional supporting context about the token, market, or other relevant information. Make sure to factor in any background knowledge, satisfy any constraints, and respect any scenarios. Your output must include: - Your reasoning about the forecast - Your predictions for the prices at the forecast horizon - Each prediction must include a timestamp and a price with lower and upper confidence bounds For the first forecast data point, use the last timestamp in the historical data so there is no gap between the historical data and the forecast (keep lower and upper confidence bounds the same as the last historical data point). Your reasoning should justify the direction, magnitude, and confidence bounds of the forecast. If you are not confident in your ability to make an accurate prediction, your forecast, including the confidence bounds, should reflect that.

Instructions flagged against the user

D7 · Harm Prevention & User Safety
“Your role is to analyze historical price data and supporting context to make token price predictions.”
The prompt instructs the system to make token price predictions without any disclaimers about financial risk, the speculative nature of cryptocurrency markets, or warnings that predictions should not be taken as financial advice. This is a high-risk financial domain where providing predictions without appropriate caveats could lead to user harm.

Questions about alphaswarm's system prompt

Does alphaswarm's system prompt contain instructions that work against the user?

Yes. 1 instruction in alphaswarm's system prompt was flagged as working against the person the product is talking to, most of them under harm prevention & user safety. Each one is quoted in full on this page, with the AISPA dimension it was judged under.

How long is alphaswarm's system prompt?

1,144 characters across 1 prompt on this page. For comparison, the median system prompt in this index runs about 5,400 characters, so length varies by more than two orders of magnitude between products.

How many versions of alphaswarm's system prompt are on record?

1. Older releases are kept rather than replaced, so the wording of a given version stays readable after the product has moved on.

Where did this alphaswarm system prompt come from?

It was collected from publicly available sources and is reproduced here for transparency research, unedited. This site does not extract prompts from products itself.

How was alphaswarm's system prompt audited?

Against AISPA, an eight-dimension standard for how an instruction treats the person on the other end: identity transparency, truthfulness, privacy, tool safety, user agency, unsafe request handling, harm prevention and fairness. This audit was ai audit. The method is described in the paper behind the standard.

How this page was made

The prompt text above is reproduced verbatim from a public source. Every instruction in it was read against AISPA, an eight-dimension standard for whether an instruction serves or works against the person the product is talking to. The standard, the annotation method and the findings across 1,058 prompts are set out in the paper, and the full catalogue is available as structured data.

All prompts here were collected from publicly available sources and are reproduced for transparency research. Browse the multi-agent systems category, the full gallery of 400+ products, or read the paper behind the AISPA standard.