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Johnhyeon

TelegramLens

by Johnhyeon
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

telegram_momentum

Read-onlyIdempotent

Detect stocks whose Telegram mentions spiked versus a baseline period, surfacing new narratives for momentum tracking by market and asset type.

Instructions

최근 언급이 기준 구간 대비 급증한 종목(새 내러티브)을 반환합니다.

종목코드 매칭 전용 — 거시·지정학·테마(예: "미국 이란", "금리") 질문은 telegram_search 사용.

Args: hours: 최근 구간(시간). 기본 6. baseline_hours: 비교 기준 구간(시간). 기본 72. top: 상위 N개(세그먼트별). 기본 15. kind: 종목 종류 — "stock"(개별주만)/"etf"(ETF만)/"all"(전체). 기본 all. market: 시장 — "KR"(국내만)/"US"(미국만)/"all"(전체). 기본 all. kind 와 조합해 국내주식·미국주식·국내ETF·미국ETF 네 갈래로 나뉩니다.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topNo
kindNo
hoursNo
marketNo
baseline_hoursNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed5 schema fields changedv0.7.0
    • removedInput schema / properties / baseline_hours / default
      Removed value: -72
    • removedInput schema / properties / hours / default
      Removed value: -6
    • removedInput schema / properties / kind / default
      Removed value: -"all"
    • removedInput schema / properties / market / default
      Removed value: -"all"
    • removedInput schema / properties / top / default
      Removed value: -15
  2. Changed1 schema field changedv0.6.1
    • addedInput schema / properties / market
      Added value: +{
+  "default": "all",
+  "title": "Market",
+  "type": "string"
+}
  3. First observedv0.4.3

TDQS

A4.6/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint=false, so the safety profile is covered. The description adds useful algorithmic context (baseline comparison, per-segment top N) but does not disclose return format, pagination, or data-freshness behavior.

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

Conciseness5/5

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

The definition is front-loaded with purpose, followed by a one-line scope/alternative statement, then a clean Args list. Every line is informative and there is no filler.

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?

For a five-parameter tool with no schema-level descriptions, the description supplies all necessary invocation details: defaults, allowed values, and the four kind/market branches. The presence of an output schema means return-value format need not be repeated.

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?

Schema description coverage is 0%, but the Args section fully documents all five parameters with defaults, allowed values, and the kind/market combination semantics. This completely compensates for the bare schema.

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?

The description opens with a precise definition: it returns stocks whose recent mentions surged relative to a baseline period, labeled as 'new narrative'. It also declares the tool is for stock-code matching only and explicitly routes macro/geopolitical/theme questions to telegram_search, distinguishing it from a sibling.

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

Usage Guidelines5/5

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

The description gives an explicit when/when-not pair with an alternative: use it for stock-code matching, and use telegram_search for macro/geopolitical/theme queries. This leaves no ambiguity about the primary intended use case.

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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