Influship

Get YouTube channel

get_youtube_channel

Read-only

Fetch a current YouTube channel by handle, channel ID, or URL.

Optionally includes recent videos. This is a metered live-data request.

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": {
      "channel": "<channel>",
      "context": "<context>",
      "llm_model": "<llm_model>"
    },
    "name": "get_youtube_channel"
  }
}

Input Schema

Name	Required	Description
`channel`	Yes	A handle, channel ID, or YouTube channel URL.
`context`	Yes	Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as "a user", "the customer", or "an account". Example: "Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution."
`llm_model`	Yes	The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. "claude-opus-4-8", "gpt-5.2"). Used for analytics only. If you do not know your model identifier with certainty, pass "unknown" — never guess.
`video_limit`	No
`include_videos`	No
`conversation_id`	No	Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.

Output Schema

Name	Required	Description	Default
`ok`	No
`data`	No
`count`	No
`results`	No
`has_more`	No
`not_found`	No
`next_cursor`	No
`suggested_followups`	No

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedNov 5, 2026

addedInput schema / properties / context

Added value: +{
+  "description": "Explain in 15-25 words, in third person, why this tool is called and how it supports the user's goal. For analytics only. You MUST describe only the abstract purpose of the tool call. NEVER include, repeat, paraphrase, or infer personal, sensitive, or identifying information from the user request or tool results, including names, emails, phone numbers, IPs, IDs, or credentials. You MUST generalize specific entities into roles such as \"a user\", \"the customer\", or \"an account\". Example: \"Retrieving a customer's recent orders to investigate a billing issue and help support determine the appropriate resolution.\"",
+  "type": "string"
+}

addedInput schema / properties / conversation_id

Added value: +{
+  "description": "Pass the exact conversation_id from the server's previous response, unchanged. The server provides it on the first call — never invent one, and do not issue parallel tool calls until you have it. Keep passing the same conversation_id for the rest of the conversation, including after later user messages or on a different task; do not reset it when the user starts a new request.",
+  "type": "string"
+}

addedInput schema / properties / llm_model

Added value: +{
+  "description": "The exact model identifier you (the assistant) are running as, taken from your system prompt or environment (e.g. \"claude-opus-4-8\", \"gpt-5.2\"). Used for analytics only. If you do not know your model identifier with certainty, pass \"unknown\" — never guess.",
+  "type": "string"
+}

changedInput schema / required

Previous value: -[
-  "channel"
-]New value: +[
+  "channel",
+  "context",
+  "llm_model"
+]

Changed2 schema fields changedOct 23, 2026
- removedOutput schema / properties / next_cursor / anyOf
```
Removed value: -[
-  {
-    "type": "string"
-  },
-  {
-    "type": "null"
-  }
-]
```
- addedOutput schema / properties / next_cursor / type
```
Added value: +[
+  "string",
+  "null"
+]
```
AddedAug 22, 2026

TDQS

B3.4/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, openWorld, non-destructive), so the description earns credit for adding that the data is 'current' (i.e., live, not cached) and that the request is 'metered', which implies cost/quota constraints an agent should ration. It also discloses that video data is optional inclusion rather than always returned. It does not quantify the metering or state failure modes, which keeps it from a 5.

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?

Three short sentences, front-loaded with the core action and input forms, with no filler. 'Current' and 'live-data' are mildly redundant, and the optional-videos clause could be one word shorter, but nothing is wasted.

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?

An output schema exists, so return values need not be explained, and the complex meta-parameters are fully documented in the schema. What is missing for a six-parameter, metered, live-data tool is anything about cost magnitude, rate limits, or when to prefer a cheaper sibling. Adequate but with clear gaps around the metering the description itself raises.

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 coverage is 67% and the schema already documents channel identifier forms, video_limit, include_videos, and the meta-parameters in detail. The description's 'by handle, channel ID, or URL' restates the channel param and 'optionally includes recent videos' loosely maps to include_videos/video_limit without adding format or default details. Baseline 3 is appropriate.

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 names a specific verb and resource (fetch a YouTube channel) and enumerates the accepted identifier forms (handle, channel ID, URL), which lets an agent distinguish it from get_youtube_video or get_youtube_channel_transcripts. It stops short of naming a sibling tool it might be confused with, such as lookup_profiles or get_creator, so it is clear but not fully differentiated.

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?

There is no explicit when-to-use or when-not-to-use guidance, and no alternative tool is named despite many overlapping siblings (get_creator, lookup_profiles, search_youtube, get_youtube_channel_transcripts). The only usage signal is the implicit cost warning in 'metered live-data request', which tells the agent to be sparing but not which tool to pick instead.

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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