Skip to main content
Glama

readComments

Extract YouTube video comments with structured provenance, enabling analysis of top-level discussions and optional threaded replies for AI-driven insights.

Instructions

Read top-level comments with optional replies and structured provenance.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
videoIdOrUrlYes
maxTopLevelNo
includeRepliesNo
maxRepliesPerThreadNo
orderNo
languageHintNo
dryRunNo
Behavior2/5

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

With no annotations provided, the description carries full burden but only mentions optional replies and provenance. It omits critical behavioral details like whether this is a read-only operation, rate limits, authentication needs, pagination, or what 'structured provenance' entails, leaving significant gaps.

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 a single, efficient sentence with zero waste. It is front-loaded with the core purpose and avoids unnecessary elaboration, making it easy to parse quickly.

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

Completeness2/5

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

Given 7 parameters with 0% schema coverage, no annotations, and no output schema, the description is insufficient. It lacks details on behavior, parameter usage, return values, and error handling, making it incomplete for a tool of this complexity.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate but adds no parameter-specific information. It vaguely references 'optional replies and structured provenance', which loosely relates to parameters like 'includeReplies' but doesn't explain their semantics, defaults, or interactions, failing to address the 7 undocumented parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Read top-level comments') and the resource ('comments'), specifying optional features like replies and provenance. It distinguishes from siblings like 'searchComments' by focusing on reading rather than searching, but doesn't explicitly contrast with 'importComments' or 'clearActiveCommentCollection'.

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

Usage Guidelines2/5

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

No guidance is provided on when to use this tool versus alternatives like 'searchComments' or 'importComments'. The description implies usage for reading comments with optional structured data, but lacks explicit context, prerequisites, or exclusions.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/rajanrengasamy/vidlens-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server