kb-research

Structured approach to finding and synthesizing information from the user's knowledge base

Opciones de instalación

De forma predeterminada está seleccionado el prompt que primero revisa el origen. Puedes cambiar a un comando directo o descargar una copia local.

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.

Un comando directo omite el prompt de revisión. Revisa el origen antes de ejecutarlo.

npx skills add https://github.com/MODSetter/SurfSense --skill kb-research

El comando permanece en una sola línea. Desplázate horizontalmente para revisarlo antes de copiarlo.

¿Prefieres una copia local? Descarga los archivos que SkillsMP tiene disponibles ahora.

Lee SKILL.md y los archivos complementarios que muestra SkillsMP antes de decidir si quieres instalarlo.

SKILL.md

Instrucciones de origen · Vista previa de solo lectura

Create polished narrated MP4 videos with Remotion in the sandbox.

Create polished PDF files for requests such as PDFs, resumes, CVs, reports, letters, one-pagers, and printable documents.

Create polished, editable Microsoft Word documents such as reports, letters, proposals, and handbooks.

name	kb-research
description	Structured approach to finding and synthesizing information from the user's knowledge base
allowed-tools	read_file, ls_tree, grep

The user asks "find/look up/research" something specifically inside their knowledge base.
The user references documents, notes, repos, or connector data they expect to exist already.
A multi-document synthesis is required (e.g., "summarize what we've discussed about X across all my notes").

Decompose the user's question into 2-4 specific, citation-worthy sub-questions.
For each sub-question, run one targeted KB search (focused on terms the user would have written, not synonyms). Open the most relevant 2-3 documents fully via read_file if their excerpts are too short.
Use grep to find supporting passages in long files instead of re-reading them end to end.
Cite every claim with the [n] label shown on the passage you used (search results and read_file output both carry them); never write a chunk id, URL, or title yourself.

Short paragraphs with inline citations.
Quoted phrases when wording matters.
An explicit "Not found in your knowledge base" callout when a sub-question has no support — never fabricate.