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prompt-compressor

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Actualizado20 de abril de 2026 a las 10:12

Compress long prompts and contexts while preserving semantic meaning — reduce token count without losing information.

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Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.

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47network

47network/Sven

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Ocupaciones relacionadasSOC

Basado en la clasificación ocupacional SOC

Desarrolladores de softwareOcupaciones informáticas y matemáticas·SOC 15-1252

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SKILL.md

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name	prompt-compressor
description	Compress long prompts and contexts while preserving semantic meaning — reduce token count without losing information.
version	0.1.0
publisher	acmecorp
handler_language	typescript
handler_file	handler.ts
when-to-use	Use when the user has a long prompt or context that needs to be shorter, or when hitting token limits.
inputs_schema	{"type":"object","properties":{"action":{"type":"string","enum":["compress","decompress_plan","benchmark"]},"text":{"type":"string"},"target_ratio":{"type":"number","description":"Target compression ratio (0.0-1.0). E.g. 0.5 means halve the token count."},"preserve_code":{"type":"boolean"}},"required":["action","text"]}
outputs_schema	{"type":"object","properties":{"result":{"type":"object"}}}

prompt-compressor

Compresses long contexts while preserving semantic information. Uses multiple techniques: abbreviation, structure extraction, key-phrase retention, and whitespace optimization.

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name	prompt-compressor
description	Compress long prompts and contexts while preserving semantic meaning — reduce token count without losing information.
version	0.1.0
publisher	acmecorp
handler_language	typescript
handler_file	handler.ts
when-to-use	Use when the user has a long prompt or context that needs to be shorter, or when hitting token limits.
inputs_schema	{"type":"object","properties":{"action":{"type":"string","enum":["compress","decompress_plan","benchmark"]},"text":{"type":"string"},"target_ratio":{"type":"number","description":"Target compression ratio (0.0-1.0). E.g. 0.5 means halve the token count."},"preserve_code":{"type":"boolean"}},"required":["action","text"]}
outputs_schema	{"type":"object","properties":{"result":{"type":"object"}}}

prompt-compressor

Compresses long contexts while preserving semantic information. Uses multiple techniques: abbreviation, structure extraction, key-phrase retention, and whitespace optimization.