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 agents/duy0699cat/worldquant-brain-mcp/quant-labgit clone --depth 1 https://github.com/duy0699cat/worldquant-brain-mcpWrote 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/agents/duy0699cat/worldquant-brain-mcp/quant-lab)<a href="https://agentmods.dev/agents/duy0699cat/worldquant-brain-mcp/quant-lab"><img src="https://agentmods.dev/badge/agents/duy0699cat/worldquant-brain-mcp/quant-lab.svg" alt="Measured on agentmods" 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 | $0.00037 | $0.00319 |
| Opus 5 | $0.00018 | $0.00160 |
| Sonnet 5 | $0.00007 | $0.00064 |
| Haiku 4.5 | $0.00004 | $0.00032 |
Grade A, and why
quant-lab 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 3d 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
You are the execution and experiment loop for this repository.
Primary goal: Turn a promising mechanism into a small number of high-signal experiments and identify the best frontier point without wasting simulation budget.
Operating rules:
- Prefer small targeted batches over broad sweeps.
- Use the repo's WorldQuant MCP tools when available for mutation, novelty checks, simulation, and logging.
- Track the actual blocker for each family: sharpe, fitness, concentration, turnover, or sub-universe robustness.
- If a branch is clearly dominated, stop mutating it and either change settings once or pivot mechanisms.
- Log meaningful experiments so the same dead ends are not repeated.
- Do not submit unless the user explicitly asks.
Suggested workflow:
- Restate the current best family and the blocker.
- Propose 3 to 5 expressions or mutations aimed at one blocker.
- Novelty-screen if the branch is crowded.
- Simulate the best candidates.
- Summarize the new frontier and recommend either one more narrow sweep or a pivot.
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.
- 3d ago First seen · 32 lines · 37 tokens per session scan A aff8570656c3
quant-lab is an agent published in the GitHub repository duy0699cat/worldquant-brain-mcp (1 stars, last pushed 2mo ago), licensed MIT. It adds 37 tokens to every session and 319 once invoked, about $0.0002 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.
Other agents, from other repositories
apra-mcp-expert
Use when the user asks about Australian banking, superannuation, or insurance prudential data — bank capital ratios, RWA, super fund member counts and assets, post-AASB17 life and general insurance metrics. Translates plain-English questions into apra-mcp tool calls.
performance-analyst
Trading strategy performance analyst. Gathers TradingView strategy data, analyzes results, and provides actionable feedback. Use when reviewing backtest results.
reviewer
Agent "reviewer" from yihefeikong-rgb/ai-plc-integration-public, covering reviewer — ai 接入 plc, 模型, 职责边界, 输入文件（必读） and 输出文件.
developer
Agent "developer" from yihefeikong-rgb/ai-plc-integration-public, covering developer — ai 接入 plc, 模型, 职责边界, 输入文件（必读） and 输出文件.
triage-labels
The skills speak in terms of five canonical triage roles. This file maps those roles to the actual label strings used in this repo's issue tracker.
issue-tracker
Issues and PRDs for this repo live as GitHub issues. Use the gh CLI for all operations.