Skip to main content
Glama

벨로그 트렌딩

velog_trending_posts
Read-only

Get trending Velog posts by selected period (day/week/month/year) to see which topics are gaining reactions and readership across the platform.

Instructions

벨로그 전체에서 지금 많이 읽히는 글. 기간(day/week/month/year)을 골라 본다. 내 글이 아니라 벨로그 전체 순위다. 무엇이 반응을 얻는지, 어떤 주제가 도는지 볼 때 쓴다. 특정 사용자의 글은 velog_list_posts, 검색은 velog_search_posts 를 쓴다. year 기간은 벨로그가 limit>20 이면 빈 결과를 주므로 20 으로 낮추고, offset 도 1000 까지만 받는다. 조정하면 응답 notes 에 적어 준다. 인증 불필요.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo가져올 글 수 (1~50, 기본 20). year 기간은 20 을 넘기면 벨로그가 빈 결과를 주어 20 으로 낮춘다
offsetNo건너뛸 글 수. 다음 페이지는 **실제로 적용된 limit** 만큼 더한다 — day·week·month 는 준 값 그대로, year 는 `min(limit, 20)` 이다. year 에서 20 을 넘겨 주면 20 으로 낮춰지므로 그때는 20씩 더해야 사이가 안 빈다. year 의 offset 상한은 1000 이고, 넘기면 1000 으로 낮춰져 같은 페이지가 나온다. 응답 첫 줄에 이번에 적용된 limit·offset 이 항상 적힌다
timeframeNo집계 기간. day=오늘, week=이번 주(기본), month=이번 달, year=올해week

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changedv0.9.2
    • addedInput schema / properties / limit / description
      Added value: +"가져올 글 수 (1~50, 기본 20). year 기간은 20 을 넘기면 벨로그가 빈 결과를 주어 20 으로 낮춘다"
    • addedInput schema / properties / offset / description
      Added value: +"건너뛸 글 수. 다음 페이지는 **실제로 적용된 limit** 만큼 더한다 — day·week·month 는 준 값 그대로, year 는 `min(limit, 20)` 이다. year 에서 20 을 넘겨 주면 20 으로 낮춰지므로 그때는 20씩 더해야 사이가 안 빈다. year 의 offset 상한은 1000 이고, 넘기면 1000 으로 낮춰져 같은 페이지가 나온다. 응답 첫 줄에 이번에 적용된 limit·offset 이 항상 적힌다"
    • addedInput schema / properties / timeframe / description
      Added value: +"집계 기간. day=오늘, week=이번 주(기본), month=이번 달, year=올해"
  2. First observedv0.3.0

TDQS

A4.7/5.0
Behavior5/5

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

Annotations already mark readOnlyHint=true and destructiveHint=false, and the description adds beyond them: no auth required, the year-period limit>20 empty-result quirk, the offset cap of 1000, and that adjusted values are reported in the response. This discloses important edge-case behavior not available from annotations alone.

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?

Front-loaded with the core concept, then scope clarification, use cases, sibling routing, and edge cases in a logical order. Every sentence earns its place and there is no filler or redundant restatement of the title.

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 read-only tool with no output schema, the description plus annotations and rich schema fully cover selection, invocation, authentication, edge cases, and response adjustment notes. Nothing an agent needs to call it correctly is missing.

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

Parameters3/5

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

Schema description coverage is 100%, and the schema already documents limit/offset/timeframe in detail, including the year edge cases. The description repeats those constraints rather than adding new parameter-level meaning, so the baseline of 3 is appropriate.

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?

Description states a specific verb+resource: '벨로그 전체에서 지금 많이 읽히는 글' (Velog-wide currently popular posts), and explicitly clarifies it is a global ranking, not the user's own posts. It also contrasts with velog_list_posts and velog_search_posts, making the purpose unmistakable.

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?

Explicitly tells when to use the tool ('무엇이 반응을 얻는지, 어떤 주제가 도는지 볼 때') and names alternatives for related cases: specific user's posts → velog_list_posts, search → velog_search_posts. Also states it is not for one's own posts, giving clear exclusions.

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