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/celineycn/quantdata-plugin/quantdata-weis-wavenpx skills add celineycn/quantdata-plugin --skill quantdata-weis-wavegit clone --depth 1 https://github.com/celineycn/quantdata-pluginWhat 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 | $0.00114 | $0.05736 |
| Opus 5 | $0.00057 | $0.02868 |
| Sonnet 5 | $0.00023 | $0.01147 |
| Haiku 4.5 | $0.00011 | $0.00574 |
Grade A, and why
quantdata-weis-wave scanned grade A with 1 finding 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 2d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl -s -H "X-API-Key: $QUANTDATA_API_KEY" \ How it starts
The opening of the file, as written. The whole thing — 376 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Quant Data — Weis Wave
An HTTP API that rebuilds the Weis Wave view of a market — price grouped into waves, each wave carrying its cumulative volume — and reports which of five classical volume-price events have fired, with the win rate each one actually measured over 16 years of data.
Base URL: https://api.quantdata.uk
Authentication
Send the header X-API-Key. Keys start with qd_.
Read the key from the environment variable QUANTDATA_API_KEY. Never write a key into
this file, into generated code, into a commit, or into a message back to the user.
export QUANTDATA_API_KEY="qd_..."
If the variable is unset, one anonymous first-look response may still succeed per source per
UTC day. It is complete, and its legacy-named free_tier object has
access_kind: "anonymous", calls_remaining_today, resets_at, and the next action.
For continued evaluation, ask the user which email address should receive a free key, then
POST https://api.quantdata.uk/v1/access/free-key with JSON:
{"email":"[email protected]","marketing_opt_in":false,"source":"agent"}
An MCP-connected agent can call quantdata_request_free_api_key instead. No login, password,
card or GUI is required. The raw qd_ key is delivered only to the inbox and never returned in
the REST or MCP result. Never invent an email address.
marketing_opt_in defaults to false and is separate from key delivery. Set it to true only
when the email owner explicitly asks for occasional product updates. A true request is only
pending. It is confirmed only if the recipient replies SUBSCRIBE to the key-delivery email;
no marketing updates are sent before confirmation. Do not report the request as a completed
subscription. A free key covers all four Quant Data endpoints, sharing 10 successful calls
per UTC day.
When a free key reaches that allowance, relay message_for_your_human, pass its checkout URL
to the person, and stop. Paid access is $149/month for every endpoint, first 3 days free. An agent
cannot complete card authentication. Checkout with the same email upgrades the existing free
key in place.
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.
- 2d ago First seen · 376 lines · 114 tokens per session scan A 67348965dba6
quantdata-weis-wave is a skill published in the GitHub repository celineycn/quantdata-plugin (1 stars, last pushed 15d ago), licensed MIT. It adds 114 tokens to every session and 5,736 once invoked, about $0.0006 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
Other skills, from other repositories
correlation-analysis
Correlation and cointegration analysis — co-movement discovery, deep return-correlation analysis, sector clustering, realized correlation, Engle-Granger / Johansen cointegration, half-life, Kalman dynamic hedge ratio, cross-market linkage analysis, and pair-trading signal generation.
ashare-pre-st-filter
A 股 ST/ST 风险预测框架 — 基于最新中报/三季报或业绩预告/快报,预测下一财年是否会因营收、利润、净资产、分红不达标而被风险警示,并将新浪监管处罚记录作为独立证据面纳入风险等级。仅适用于 A 股,不预测财务造假。.
credit-analysis
固收与信用分析:信用债评级、利差分析、违约风险评估、城投债研究、可转债定价与策略。.
geopolitical-risk
Geopolitical risk analysis: quantify crisis signals, identify precursors, and build event-driven strategies for war, sanctions, and supply disruption scenarios.
vibe-trading
Professional finance research toolkit — backtesting (10 engines + benchmark comparison panel), factor analysis, Alpha Zoo (462 pre-built alphas across qlib158/alpha101/gtja191/academic/fundamental), options pricing, 90 finance skills, 30 multi-agent swarm teams, Trade Journal analyzer, and Shadow Account (extract →…
etf-analysis
ETF分析:产品筛选、费率对比、跟踪误差、流动性评估、策略应用与中国市场ETF量化配置框架。.