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 yugef3h/leo-skills --skill chatbi-mvpgit clone --depth 1 https://github.com/yugef3h/leo-skillsWrote 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/yugef3h/leo-skills/chatbi-mvp)<a href="https://agentmods.dev/skills/yugef3h/leo-skills/chatbi-mvp"><img src="https://agentmods.dev/badge/skills/yugef3h/leo-skills/chatbi-mvp/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/yugef3h/leo-skills/chatbi-mvp"><img src="https://agentmods.dev/badge/skills/yugef3h/leo-skills/chatbi-mvp.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 | $0.00061 | $0.01413 |
| Opus 5 | $0.00030 | $0.00707 |
| Sonnet 5 | $0.00012 | $0.00283 |
| Haiku 4.5 | $0.00006 | $0.00141 |
Grade A, and why
chatbi-mvp 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 12d 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.
How it starts
The opening of the file, as written. The whole thing — 115 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ChatBI MVP Architecture
Overview
Build a ChatBI system: user asks questions in natural language → system generates SQL → executes → displays interactive charts with AI insights.
Architecture: NL → S2SQL (semantic SQL / MQL) → Physical SQL. LLM generates S2SQL using business terms (bizName), a deterministic Translator converts to physical SQL. LLM never touches physical table/column names.
Tech stack assumed: React (frontend) + Python/FastAPI (backend). Architecture is language-agnostic.
Five Core Layers
User: "最近7天各分区播放量怎么样"
│
▼
┌─ Layer 3: RAG ────────────────┐ Trie + Embedding recall
│ "播放量" → views (metric) │ Identify schema elements
│ "分区" → category (dim) │ in user query
│ "最近7天" → DateConf{-7d} │
└───────────────┬───────────────┘
│
▼
┌─ Layer 1: NL → S2SQL → SQL ──┐ 5-stage pipeline
│ MAPPING → PARSING → │ LLM generates S2SQL (bizName)
│ CORRECTING → TRANSLATING │ Translator → physical SQL
│ → EXECUTE │
└───────────────┬───────────────┘
│
┌───────┴───────┐
▼ ▼
┌─ Layer 2 ───┐ ┌─ Layer 5 ──────────┐
│ Multi-turn │ │ Attribution │
│ Context save │ │ LLM summary + YoY │
│ + LLM rewrite│ │ + drill-down recs │
└──────────────┘ └─────────────────────┘
│ │
└───────┬───────┘
▼
┌─ Layer 4: Visualization ──────┐
│ Auto chart type → ECharts │
│ User can toggle chart/table │
│ Drill-down → re-query │
└───────────────────────────────┘
File Index
This skill is split into focused files. Read in order, or jump to what you need.
Core Architecture (read first)
| File | Contents | When to read |
|---|---|---|
data-models.md |
All shared POJOs: SemanticSchema, SchemaMapInfo, SemanticParseInfo, QueryResult | Always start here — these connect every layer |
nl2sql-pipeline.md |
Layer 1 in detail: 5-stage pipeline, prompt template, self-consistency, corrector chain, S2SQL→physical translator | Core of the system |
wiring.md |
How all layers connect: full request flow, plugin registration, DB tables | When you need to see the big picture |
What ships with it
11 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 12d ago First seen · 115 lines · 61 tokens per session scan A 30d12f88c1e7
chatbi-mvp is a skill published in the GitHub repository yugef3h/leo-skills (11 stars, last pushed 5d ago), licensed MIT. It adds 61 tokens to every session and 1,413 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 2026-08-30.
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