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 skills add malue-ai/dazee-small --skill raglitegit clone --depth 1 https://github.com/malue-ai/dazee-smallWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/malue-ai/dazee-small/raglite)<a href="https://agentmods.dev/skills/malue-ai/dazee-small/raglite"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/raglite/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/malue-ai/dazee-small/raglite"><img src="https://agentmods.dev/badge/skills/malue-ai/dazee-small/raglite.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00022 | $0.00476 |
| Opus 5 | $0.00011 | $0.00238 |
| Sonnet 5 | $0.00004 | $0.00095 |
| Haiku 4.5 | $0.00002 | $0.00048 |
Grade A, and why
raglite 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 9d ago.
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
RAGLite 本地知识检索
将文档蒸馏为结构化 Markdown 并建立本地索引，实现快速知识检索。无需外部向量数据库。
使用场景
- 用户说「帮我把这些文档建成知识库，方便以后查询」
- 用户有大量 PDF/Markdown 文档需要快速搜索
- 需要基于私有文档回答问题（RAG 场景）
- 与知识库类 Skill 配合，提供语义搜索能力
执行方式
安装
pip install raglite
索引文档
from raglite import RAGLiteConfig, insert_document
config = RAGLiteConfig(
db_url="sqlite:///~/Documents/xiaodazi/raglite.db",
)
insert_document(
doc_path="report.pdf",
config=config,
)
检索
from raglite import retrieve_chunks, rerank_chunks
chunks = retrieve_chunks(
query="公司的营收增长情况",
num_chunks=10,
config=config,
)
reranked = rerank_chunks(query="公司的营收增长情况", chunk_ids=[c.id for c in chunks], config=config)
RAG 问答
from raglite import rag
response = rag(
prompt="根据文档，公司去年的营收是多少？",
config=config,
)
print(response)
支持的文档格式
- PDF（通过 MinerU 或 PyPDF 解析）
- Markdown
- 纯文本
输出规范
- 索引完成后显示文档数量和索引大小
- 检索结果附带来源文档和页码引用
- 回答时明确标注信息出处
- 数据库存储在本地，不上传
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.
- 9d ago First seen · 87 lines · 22 tokens per session scan A 57634ccec9ff
raglite is a skill published in the GitHub repository malue-ai/dazee-small (36 stars, last pushed 5mo ago), licensed MIT. It adds 22 tokens to every session and 476 once invoked, about $0.0001 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 2026-09-03.
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