anti-hype-filter（反炒作过滤器）

SKILL: anti-hype-filter

Purpose

Detect and neutralize hype cycles before they distort system integrity by stripping emotional triggers and replacing them with structural analysis.

When to Use

• "guaranteed", "moon", "100x", "alpha" style language
• Urgency without substance ("now or never")
• Social proof without evidence
• Claims that minimize risk or constraints

Inputs

• text (required): message to evaluate
• context (optional):

- domain (token|product|governance|community)

• policy (required):

- hype_terms (optional list; if omitted, use the embedded default set in this skill) - max_response_words (default 100)

Steps

1. Extract key claims (1-5).
2. Detect hype triggers:

- urgency framing - certainty language - vague upside claims - social proof substitution

1. Classify:

- signal, noise, or manipulation_risk

1. Rewrite the message into a verifiable form:

- replace certainty with uncertainty - add required missing variables (data window, metrics, constraints)

1. Draft a minimal response that:

- does not repeat hype memes verbatim - demands evidence and risk disclosure

Validation

• If classification is manipulation_risk, provide at least 1 falsifiable request for evidence.
• Do not amplify hype phrases; paraphrase instead.

Output

• anti_hype_result:

- classification ("signal"|"noise"|"manipulation_risk") - detected_triggers (list) - missing_information (list) - rewrite (verifiable version) - response_draft (string)

Safety Rules

• Never accuse individuals of malice without evidence; label as "risk" not "intent".
• No financial promises.
• No deception; no fabricated data.

Example

Input: "This will 100x in 2 weeks, everyone knows." Output: manipulation_risk, missing evidence, rewrite into metrics/timeframe/assumptions, and a short demand for proof + risk disclosure.