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HPSILab Quant Finance

by io.github.haiyunsky

Stock Research Report

generate_stock_research_report

Full markdown research report with five stock-report charts. Pro tool ($0.35/call via x402 for anonymous callers; free within plan limits for signed-in accounts, subject to a monthly report quota).

Runs analyze_stock and stock-report image generation concurrently, then
renders a presentation-ready markdown report (direction, direction score, bullish /
bearish factors, source-tool status, and the five chart embeds). The markdown
is returned for display and the same data is mirrored in structured JSON.

Signed-in hpsilab users call this within their plan's free rate limits.
Anonymous / tokenless agents pay per call via x402 (USDC on Base) when
payments are enabled — send the x402 payment in the request _meta.

Args:
    symbol: Stock symbol, e.g. "RXRX".
    refresh: Bypass the backend's fresh IV cache for the IV-driven modules.
        Defaults to False.
    force_images: Force a fresh image render instead of reusing the backend's
        image cache. Defaults to False.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
symbolYes
refreshNo
force_imagesNo

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses that it runs other tools concurrently, returns both markdown and JSON, and mentions the payment model. Adds context beyond annotations (e.g., non-mutating behavior despite readOnlyHint=false).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Well-structured with purpose, cost, execution details, then arguments. Slightly verbose but all information is relevant and well-organized.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Covers all aspects: output format (markdown + JSON), cost model, parameter details, and notes on caching. No missing information for a tool of this complexity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description fully explains all parameters: symbol with example, refresh as cache bypass, force_images as fresh render. No ambiguity.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it generates a full markdown research report with five charts, distinguishes from siblings by describing it as a composite tool that runs analyze_stock and image generation concurrently.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Explains cost and authentication requirements, implying when to use this tool vs. alternatives, but does not explicitly state when not to use or enumerate alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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TDQS

A4.4/5.0
Disambiguation5/5

Every tool has a clearly distinct purpose, from individual analytics like AI prediction and IV radar to aggregation and report generation. No overlapping functionality.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case, with verbs like get_, generate_, and analyze_. No mixing of conventions.

Tool Count5/5

9 tools is well-scoped for a quant finance server, covering diverse analytics and outputs without being excessive or sparse.

Completeness4/5

Covers major quant finance analyses and reporting. Minor gap: no raw data access tools, but the surface is comprehensive for the intended use case.

Resources