networklytics-mcp

get_analysis_by_id

Retrieve YouTube comment network analysis by ID to access influencer rankings, community detection, sentiment insights, and AI-generated data from NetworkLytics.

Instructions

Retrieve a YouTube comment network analysis by its ID. Requires API key authentication (set NETWORKLYTICS_API_KEY environment variable). Returns the same structured data as get_shared_analysis.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "analysis_id": "<analysis_id>"
    },
    "name": "get_analysis_by_id"
  }
}

Input Schema

Name	Required	Description	Default
`analysis_id`	Yes	The numeric analysis ID from NetworkLytics

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.1Apr 13, 2026

TDQS

B3.4/5.0

Behavior3/5

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

With no annotations provided, the description carries the full burden. It discloses authentication requirements (API key via environment variable) and return behavior (structured data similar to get_shared_analysis), which adds useful context. However, it lacks details on error handling, rate limits, or other behavioral traits like response format specifics.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized with two sentences that are front-loaded with key information (retrieval action and authentication). It avoids unnecessary details, though it could be slightly more structured by separating usage guidelines from behavioral notes.

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

Completeness3/5

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

Given the tool's low complexity (1 parameter, no output schema, no annotations), the description is somewhat complete by covering purpose and authentication. However, it lacks output details (e.g., what the structured data includes) and doesn't fully address sibling tool differentiation, leaving gaps for an AI agent.

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?

The schema description coverage is 100%, so the schema already documents the single parameter 'analysis_id' as a numeric ID from NetworkLytics. The description adds no additional meaning beyond this, such as format examples or constraints, meeting the baseline for high schema coverage.

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 ('Retrieve') and resource ('YouTube comment network analysis by its ID'), making the purpose understandable. However, it doesn't explicitly distinguish this tool from its sibling 'get_shared_analysis' beyond noting they return similar data, missing a direct comparison of when to use each.

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 by specifying that it retrieves by ID and requires API key authentication, but it doesn't provide explicit guidance on when to use this tool versus alternatives like 'get_shared_analysis' or 'get_api_info'. No exclusions or clear alternatives are mentioned.

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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