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Johnhyeon

TelegramLens

by Johnhyeon
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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telegram_block_name

Add a stock to the blocklist to stop its name from being miscounted in Telegram stock mention trends. Supports Korean 6-digit codes and US cashtags, with dry-run preview.

Instructions

종목을 차단 목록에 추가합니다(확인 표기가 있을 때만 인정하도록).

국내 6자리 코드와 미국 티커를 모두 받습니다. 국내는 이름 단독 매칭을 막고 본문에 코드가 있을 때만 인정하며, 미국은 bare 매칭을 막고 cashtag($NVDA)로 쓸 때만 인정합니다.

dry_run=True 면 아무것도 바꾸지 않고, 최근 30일 집계에서 빠질 언급 수와 원문 표본을 보여줍니다. 실제 적용 시 같은 조건으로 제거하므로 두 건수는 일치합니다. 적용 후에는 telegram_trending / telegram_fp_candidates 를 다시 돌려 순위 변화와 오탐 회귀를 확인하세요.

Args: code: 6자리 종목코드(예: 001680) 또는 미국 티커(예: ASIC). note: 메모(예: '대상 = target/object 충돌'). dry_run: True 면 미리보기만(기본 False).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
codeYes
noteNo
dry_runNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changedv0.7.0
    • removedInput schema / properties / dry_run / default
      Removed value: -false
    • removedInput schema / properties / note / default
      Removed value: -""
  2. Changed1 schema field changedv0.6.1
    • addedInput schema / properties / dry_run
      Added value: +{
+  "default": false,
+  "title": "Dry Run",
+  "type": "boolean"
+}
  3. First observedv0.4.3

TDQS

A4.6/5.0
Behavior5/5

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

Beyond the sparse annotations, the description discloses that real application modifies the block list, dry_run makes no changes, and the dry-run removal count exactly matches actual removal. It also specifies the exact matching policy (Korean names require a code in the body; US names require a cashtag), which is important behavioral context. No contradiction with annotations.

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 well-structured: purpose sentence, bold matching-policy block, dry-run workflow, and a compact Args section. Each sentence earns its place and the most important behavioral constraint is front-loaded.

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 3-parameter tool with an output schema available, the description covers input formats, matching conditions, dry-run semantics, count consistency, and post-run verification steps. Nothing an agent needs to call it correctly or confirm the result is missing.

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%, so the description carries full responsibility for parameters, and it succeeds. code gets format and examples, note gets a concrete example, and dry_run gets its default and preview behavior. This adds meaning far beyond the bare schema properties.

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?

States a specific action: '종목을 차단 목록에 추가합니다' – adding a stock to the block list – and clarifies scope with Korean 6-digit codes vs US tickers. The matching rules make the tool's purpose distinct from generic search or alias tools, so an agent can tell what it does.

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

Usage Guidelines3/5

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

The description gives clear operating guidance: dry_run previews the count and samples, and after applying the block the agent should rerun telegram_trending / telegram_fp_candidates. However, it never explicitly contrasts this with siblings like telegram_add_alias or states when blocking should be chosen over alternatives, so the selection guidance is implied rather than direct.

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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