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Johnhyeon

StockLens

by Johnhyeon
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Remote

get_reports

Read-onlyIdempotent

Retrieve securities analyst reports for stocks, market, industry, or economy topics. Specify a stock code or report category to get recent research and analyst opinions.

Instructions

증권사리포트 — 종목·시황·산업·경제 등 증권사 분석 리포트.

"리포트", "증권사 분석", "애널리스트 의견", "리서치" 같은 질문에 사용합니다.

종목 리포트는 code 로, 종목을 가리지 않는 갈래는 kind 로 부릅니다. "오늘 증권가가 시장을 어떻게 보나" 같은 질문이 후자입니다.

Args: code: 종목코드 6자리 (예: "005930"). 종목 리포트를 볼 때만. count: 가져올 리포트 수 (기본 5, 최대 10) kind: 종목 대신 갈래로 볼 때. market(시황) | invest(투자전략) | economy(경제) | debenture(채권) | industry(산업) | company(종목)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeNo
kindNo
countNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv1.1.3
    • removedInput schema / properties / code / default
      Removed value: -""
    • removedInput schema / properties / count / default
      Removed value: -5
    • removedInput schema / properties / kind / default
      Removed value: -""
  2. Changed3 schema fields changedv1.1.0
    • addedInput schema / properties / code / default
      Added value: +""
    • addedInput schema / properties / kind
      Added value: +{
+  "default": "",
+  "title": "Kind",
+  "type": "string"
+}
    • removedInput schema / required
      Removed value: -[
-  "code"
-]
  3. First observedv0.4.0

TDQS

A4.1/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint, and destructiveHint=false, so the safety profile is covered. The description adds count defaults/maximums and query-mode distinctions, but it does not disclose additional behavioral traits such as auth requirements, rate limits, or result ordering. With annotations present, the added behavioral context is adequate but not rich.

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?

The description is well-structured and front-loaded with the purpose, followed by usage triggers and parameter details. There is slight redundancy between the prose explanation and the Args section, but each paragraph earns its place and the format is scannable.

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?

Given the annotations and output schema, the description is complete enough for an agent to invoke the tool correctly. It covers parameter semantics, mutual exclusivity of `code` vs `kind`, allowed enum values, count limits, and example queries. No essential missing information prevents correct selection or invocation.

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?

The input schema is bare with 0% description coverage, so the description carries the full burden. It thoroughly explains `code` as a 6-digit stock code, `kind` with all enum values (market, invest, economy, debenture, industry, company), and `count` with default and maximum. This fully compensates for the schema's lack of parameter descriptions.

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

Purpose4/5

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

The description clearly states the tool retrieves brokerage research reports across stocks, market, industry, and economy. It distinguishes stock-specific usage via `code` from category-based usage via `kind`, but it does not explicitly contrast with sibling tools like `get_report_content` or `get_consensus`.

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?

It provides concrete query triggers such as '리포트', '증권사 분석', and '애널리스트 의견', plus an example of a market-sentiment question. It clarifies when to use `code` vs `kind`, but it does not name alternatives or state when not to use this tool.

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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