using-ragkit

A session-start guide for RagKit, a project knowledge-base search system that combines vector, word-based, and metadata search.

In plain words
What is it for?
Use it as a reference for searching, building an index, checking index health, or measuring retrieval accuracy.
Why use it?
It tells the coding agent which RagKit operation to use and keeps it from bypassing the supported search process or reading the index files directly.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/qxbyte/pluginhub/using-ragkit
Any agent
npx skills add qxbyte/pluginhub --skill using-ragkit
Clone the repo
git clone --depth 1 https://github.com/qxbyte/pluginhub

Made for: Claude Code, Codex.

Per session 62 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 453 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00062 $0.00453
Opus 5 $0.00031 $0.00227
Sonnet 5 $0.00012 $0.00091
Haiku 4.5 $0.00006 $0.00045

Measured yesterday against content hash 15b65bdf508f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

using-ragkit scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

plugins/ragkit/skills/using-ragkit/SKILL.md · 20 lines

What it actually says

using-ragkit — ragkit 可用性说明(会话启动注入)

本技能是 ragkit 的会话启动 advisory。在 Kimi Code 由清单的 sessionStart.skill 于会话开始时注入;在有 SessionStart hook 的宿主(Claude Code / CodeBuddy)由 hook 注入等价文案,无需本技能。

RagKit 可用:对项目 knowledge-base/ 做多路检索(向量 + 词汇 + 元数据,RRF 融合)。四个技能:

  • ragkit:query — 检索,返回定位卡片(非事实来源,仅用于快速定位真实代码)。
  • ragkit:embed — 构建 / 更新向量索引。
  • ragkit:status — 索引健康 / drift。
  • ragkit:eval — 检索精度评估。

用户要检索 / 建索引 / 查健康时,用 Skill 工具(或宿主等价的 skill 调用机制)按名调用对应技能(/ragkit:* 或直接按名,无需去找命令文件)。

硬约束(防脱轨):① 只按名调技能,绝不在文件系统里搜 skill / 脚本文件——插件文件在插件缓存目录、不在你的项目里,技能内部会自己定位脚本;② 检索只能调 RagKit 的脚本,严禁自己读 .ragkit 向量文件、装 numpy、或用 embedding API 手搓相似度(结果会错且不可复现);③ 脚本定位 / 运行失败 → 停下报确切错误,不要绕过、不要自己实现。

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 20 lines · 62 tokens per session scan A 15b65bdf508f

Subscribe to this mod's changes

using-ragkit is a skill published in the GitHub repository qxbyte/pluginhub (3 stars, last pushed 27d ago), licensed MIT. It adds 62 tokens to every session and 453 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

douyin-favorites-to-knowledge

将用户已授权账号中的抖音视频收藏或用户明确指定的喜欢列表配置并同步到本地 Markdown 或 Obsidian 知识库;默认收藏,只有用户明确说喜欢/点赞才切换来源。首次明确选择推荐的 SiliconFlow转录、本地 Whisper 或不转录。不得绕过登录、访问他人账号或泄露 Cookie 与私密数据。.

tars1230/douyin-favorites-to-knowledge · 92 tokens

knowledge-extractor

Entrevista a un experto de dominio (SME) para extraer su conocimiento técnico tácito y sintetizarlo en una Skill reutilizable. Se activa PROACTIVAMENTE ante 3 situaciones: (1) Frustración — el usuario se queja de código, arquitectura o falta de estándares; (2) Ambigüedad sin Reglas — se pide un refactor profundo pero…

Vasallo94/obsidian-mcp-server · 156 tokens

MCP Developer

Skill para desarrollar, mantener y extender el servidor MCP de Obsidian. Incluye patrones de código, arquitectura, testing y gestión de paquetes.

Vasallo94/obsidian-mcp-server · 33 tokens

Python Patterns

Buenas prácticas y patrones de desarrollo Python para el proyecto MCP. Incluye estándares de código, patrones arquitectónicos, y convenciones.

Vasallo94/obsidian-mcp-server · 29 tokens

Refactoring

Guía para refactorizar código Python de forma segura y efectiva. Incluye técnicas de refactoring, detección de code smells, y mejoras.

Vasallo94/obsidian-mcp-server · 33 tokens

Test Runner

Skill para ejecutar y gestionar tests. Incluye patrones de testing, fixtures comunes, y estrategias de debugging de tests fallidos.

Vasallo94/obsidian-mcp-server · 28 tokens