Execute qualquer Skill no Manus
com um clique

Execute qualquer Skill no Manus com um clique

query

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Atualizado8 de julho de 2026 às 08:32

Use when retrieving from a project knowledge-base/ — multi-channel RAG recall (vector plus lexical plus metadata, RRF-fused) returning locate-pointer cards; multi-round and multi-angle querying allowed. Trigger /ragkit:query, or called by name by workflows like specode. Building or refreshing the index instead uses ragkit:embed.

Instalação

Instalar com Codex ou Claude Copie este prompt, cole no Codex, Claude ou outro assistente e deixe que ele revise a página da skill e instale para você.

Executar no Manus

Fonte

qxbyte

qxbyte/pluginhub

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Executar no Manus

Ocupações relacionadasSOC

Baseado na classificação ocupacional SOC

Desenvolvedores de softwareInformática e Matemática·SOC 15-1252

SKILL.md

readonly

name	query
description	Use when retrieving from a project knowledge-base/ — multi-channel RAG recall (vector plus lexical plus metadata, RRF-fused) returning locate-pointer cards; multi-round and multi-angle querying allowed. Trigger /ragkit:query, or called by name by workflows like specode. Building or refreshing the index instead uses ragkit:embed.

RagKit Query

对项目 knowledge-base/ 做多路召回（向量+词汇+元数据，RRF 融合），返回定位卡片。

执行

脚本在本插件的 scripts/ 目录（本 skill 目录的上两级）；用本 skill 的 base directory 把下面的相对路径拼成绝对路径执行。

sh ../../scripts/run.sh ../../scripts/ragkit.py \
   query '<检索词>' --kb <项目根>/knowledge-base

检索词由你根据用户问题/需求自行提炼：优先用页面名、字段名、接口路径、功能域词。
允许多轮、多角度：一轮不够就换角度再查（按页面查 / 按字段查 / 按调用链查），直到定位充分或确认无相关知识。
需要程序化消费时加 --json；--top N 调数量。

结果使用纪律（硬约束）

卡片是定位指针，非事实来源——命中后用「路径」Read 原文，再跳到真实代码验证；禁止仅凭卡片摘要下结论。
tag/词面命中 ≠ 语义相关：逐条判断该知识点的改动类型/语义是否真适用，不适用就丢弃。
独立 RAG 用法（用户直接提问系统历史逻辑）：召回 → Read 命中文档 → 综合整理回答，并注明来源文档路径。

降级与错误（stderr 信号，固定文案）

无可用向量后端：结果仍有效（词汇+元数据路）；stderr 会带一个 ╭─ RagKit ─╮ 提示块，原样转述给用户（不改写、不省略）。
索引不存在：提示用户先跑 /ragkit:embed。
model_mismatch / index_stale：提示用户重跑 /ragkit:embed（必要时 --rebuild）。

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name	query
description	Use when retrieving from a project knowledge-base/ — multi-channel RAG recall (vector plus lexical plus metadata, RRF-fused) returning locate-pointer cards; multi-round and multi-angle querying allowed. Trigger /ragkit:query, or called by name by workflows like specode. Building or refreshing the index instead uses ragkit:embed.

RagKit Query

对项目 knowledge-base/ 做多路召回（向量+词汇+元数据，RRF 融合），返回定位卡片。

执行

脚本在本插件的 scripts/ 目录（本 skill 目录的上两级）；用本 skill 的 base directory 把下面的相对路径拼成绝对路径执行。

sh ../../scripts/run.sh ../../scripts/ragkit.py \
   query '<检索词>' --kb <项目根>/knowledge-base

检索词由你根据用户问题/需求自行提炼：优先用页面名、字段名、接口路径、功能域词。
允许多轮、多角度：一轮不够就换角度再查（按页面查 / 按字段查 / 按调用链查），直到定位充分或确认无相关知识。
需要程序化消费时加 --json；--top N 调数量。

结果使用纪律（硬约束）

卡片是定位指针，非事实来源——命中后用「路径」Read 原文，再跳到真实代码验证；禁止仅凭卡片摘要下结论。
tag/词面命中 ≠ 语义相关：逐条判断该知识点的改动类型/语义是否真适用，不适用就丢弃。
独立 RAG 用法（用户直接提问系统历史逻辑）：召回 → Read 命中文档 → 综合整理回答，并注明来源文档路径。

降级与错误（stderr 信号，固定文案）

无可用向量后端：结果仍有效（词汇+元数据路）；stderr 会带一个 ╭─ RagKit ─╮ 提示块，原样转述给用户（不改写、不省略）。
索引不存在：提示用户先跑 /ragkit:embed。
model_mismatch / index_stale：提示用户重跑 /ragkit:embed（必要时 --rebuild）。