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bulatko

vk-mcp-server

by bulatko

See who reacted

vk_likes_get
Read-onlyIdempotent

List users who liked or reacted to a VK object (post, comment, photo, video) with reaction counts.

Instructions

List the users who liked or reacted to an object — a post, comment, photo or video — with counts per reaction. owner_id is negative for a community; item_id is the post or object ID.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
typeYesObject type
countNoNumber of users to return (max 1000)
offsetNoOffset for pagination
item_idYesObject ID
owner_idNoOwner ID of the object (negative for community)
reaction_idNoFilter by reaction: 0 — like ❤️, 1 — laugh 😂, 2 — wow 😮, 3 — admiration 🔥, 4 — angry 😡, 5 — sad 😢

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoTotal number of matches on VK, which is usually larger than the returned page
itemsYesUsers who reacted to the object
paginationNoWhere this page sits in the whole result. Call the tool again with offset set to next_offset to continue; when next_offset is null there is nothing left to fetch.
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive behavior. The description adds behavioral context about returning counts per reaction and parameter specifics (e.g., owner_id negative for community), going beyond the schema without contradicting 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?

Two sentences efficiently convey the tool's purpose and a key parameter detail. No waste, front-loaded with the core action.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (6 params, 2 required, output schema, comprehensive annotations), the description covers the main purpose and essential parameter nuances. It does not discuss pagination but schema handles that. Adequate for a well-specified tool.

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 descriptions cover 100% of parameters. The tool description adds minimal additional meaning (e.g., clarifying owner_id and item_id), but this information is already present in the schema, providing no significant extra value.

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 clearly states the tool lists users who liked/reacted to an object with counts per reaction, using specific verbs and distinguishing from sibling tools that handle other operations like posts or users.

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 implies usage for retrieving reaction data but lacks explicit guidance on when to use this tool versus alternatives or when not to use it. No comparison to sibling tools is provided.

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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