Description

Detects user prompts that are unusually long and full of low-signal "fluff" words (please, kindly, thanks, basically, essentially, definitely, absolutely, simply, very, quite, somewhat, certainly). Long verbose prompts inflate input tokens on every turn — and where compression skills are available (e.g. caveman/cavecrew), the user is paying the verbosity tax twice (once on the user message, once on the system instructions).

When Triggered

{{count}} verbose prompts ({{pct}}) of length ≥{{thresholds.minMessageLength}} chars contained 2+ filler words. These prompts could be rewritten to half the size with no loss of meaning.

How to Improve

Be terse and structured. Replace "please could you kindly write a function that basically just adds two numbers" with "write add(a,b)". Use bullet points instead of paragraphs. Drop pleasantries — Copilot doesn't care, and you pay for every token. Consider installing a compression skill like caveman/cavecrew to compress sub-agent results.

Examples

"{{messageText | truncate:80}}" ({{messageLength}} chars)

Detection Logic

scan: requests
match: messageLength >= thresholds.minMessageLength AND matches(messageText, "(?i)\\b(please|kindly|thanks|thank you|basically|essentially|definitely|absolutely|simply|very|quite|somewhat|certainly|actually|literally)\\b.*\\b(please|kindly|thanks|thank you|basically|essentially|definitely|absolutely|simply|very|quite|somewhat|certainly|actually|literally)\\b") AND hasSkillByPattern(allReqs, "(?i)cavecrew|caveman|compress") == 0
aggregate: ratio
check: ratio > thresholds.maxRatio AND count > thresholds.minSample
examples: "{{messageText | truncate:80}}" ({{messageLength}} chars)