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.
npx agentmods add skills/qxbyte/pluginhub/querynpx skills add qxbyte/pluginhub --skill querygit clone --depth 1 https://github.com/qxbyte/pluginhubWhat 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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00071 | $0.00631 |
| Opus 5 | $0.00036 | $0.00316 |
| Sonnet 5 | $0.00014 | $0.00126 |
| Haiku 4.5 | $0.00007 | $0.00063 |
Grade A, and why
query 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.
What it actually says
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）。向量后端调用失败（vector_error）：云端密钥失效/网络异常等，query 不崩溃，已自动降级词汇+元数据路，结果仍有效；stderr 带失败详情，转述并提示用户检查密钥（环境变量是否设对、是否用了完整 key）或网络后重试。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）。
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.
- yesterday First seen · 35 lines · 71 tokens per session scan A 9cf564b92a12
query is a skill published in the GitHub repository qxbyte/pluginhub (3 stars, last pushed 27d ago), licensed MIT. It adds 71 tokens to every session and 631 once invoked, about $0.0004 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.
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