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Read-onlyIdempotent

Search full message text and linked article snippets from Telegram channels using keywords or topics. Filter by time window or specific channel to find relevant discussions.

Instructions

원문 메시지를 키워드/주제로 전문검색합니다('내용' 축 도구).

종목코드가 안 붙은 거시·산업·테마 글도 본문 키워드로 찾습니다(예: "반도체 HBM", "금리 인하"). 여러 단어는 공백 구분 AND 매칭, 3글자 이상이 정확·빠름. 글에 붙은 링크의 제목·설명·발췌까지 함께 뒤집니다 — 본문은 제목 한 줄이고 내용은 기사 안에 있는 글도 잡힙니다(결과의 matched_in: "text" | "link").

Args: query: 검색 키워드(여러 단어는 공백 구분, AND 매칭). hours: 검색 시간 범위(시간). 기본 72. limit: 최대 결과 수. 기본 30. channel: 특정 채널 username(@ 제외)으로 한정. 생략 시 전체. in_links: 링크 내용(제목·설명·발췌)까지 검색. 기본 true. link_body: true 면 결과에 링크 본문 발췌까지 싣습니다. 기본 false(제목·설명만).

Input Schema

TableJSON Schema

Name	Required	Description	Default
`hours`	No
`limit`	No
`query`	Yes
`channel`	No
`in_links`	No
`link_body`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed7 schema fields changedv0.7.0Sep 19, 2026
- removedInput schema / properties / channel / anyOf
```
Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
```
- removedInput schema / properties / channel / default
```
Removed value: -null
```
- addedInput schema / properties / channel / type
```
Added value: +"string"
```
- removedInput schema / properties / hours / default
```
Removed value: -72
```
- addedInput schema / properties / in_links
```
Added value: +{
+  "title": "In Links",
+  "type": "boolean"
+}
```
- removedInput schema / properties / limit / default
```
Removed value: -30
```
- addedInput schema / properties / link_body
```
Added value: +{
+  "title": "Link Body",
+  "type": "boolean"
+}
```
First observedv0.4.3Jul 8, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Beyond readOnly/idempotent annotations, it discloses meaningful behavior: multi-word AND matching, the 3-character performance note, searching through attached link titles/descriptions/excerpts, and the matched_in result field distinguishing 'text' from 'link'. This gives the agent useful expectations about search scope and result semantics.

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 description is dense but well-organized: a clear lead sentence, brief behavioral notes, and a compact parameter list. Every line adds operational value, with no filler or repetition of annotation facts.

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 6-parameter search tool with zero schema descriptions, this is complete: it covers scope, matching semantics, link handling, defaults, and result-field hints. The output schema supplies return structure, so the description does not need to repeat it.

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 coverage is 0%, but the Arg list fully compensates by explaining all six parameters: query keywords, hours range with default 72, limit with default 30, channel restriction with @ exclusion, in_links behavior, and link_body excerpt inclusion. This adds substantial meaning beyond the bare schema titles.

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 specific verb and resource: '원문 메시지를 키워드/주제로 전문검색합니다' (full-text search of original messages by keyword/topic). It also positions itself as the '내용' (content) axis tool, distinguishing it from siblings that focus on velocity, momentum, or channel metadata.

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?

The description gives clear context on when to use this tool: for searching message content and link bodies, including macro/industry/theme posts without stock codes. It does not explicitly name alternatives or state when not to use it, but the 'content axis' framing and search-oriented behavior provide solid usage direction.

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