Influship

Get TikTok video transcript

get_tiktok_video_transcript

Read-only

Fetch or generate a normalized TikTok video transcript.

Returns plain text and timestamped segments. A previously collected transcript can be reused. Each successful request costs 2.5 account credits, including a reused result, and may take longer when transcription must be generated.

Input Schema

Name	Required	Description
`url`	Yes
`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.
`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: -[
-  "url"
-]New value: +[
+  "url",
+  "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 12, 2026

TDQS

A3.7/5.0

Behavior4/5

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

Goes well beyond the annotations by disclosing a concrete billing cost (2.5 account credits per successful request, including reused results), variable latency when transcription must be generated, and an internal reuse/caching behavior. The annotations only say readOnly/openWorld/non-destructive, so the cost and latency disclosure is real added value. It stops short of stating failure/charge behavior for unsuccessful requests or any rate limits, which would have made this 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?

Four short sentences with the core action front-loaded and the cost/latency caveats grouped at the end; nothing is padded. The only redundancy is restating the return shape ('plain text and timestamped segments') when an output schema already exists, though it is brief enough not to be wasteful.

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?

For a single-item fetch tool with an output schema and full annotations, the description covers the ingredients an agent needs to decide and to budget: what it returns, cost, and slow-path latency. The remaining gap is sibling disambiguation against get_tiktok_video_transcripts and get_tiktok_video_captions, which an agent in this 40-tool namespace would plausibly confuse.

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 75%, with context, llm_model, and conversation_id documented at length in the schema itself, so the description carries no obligation to restate them. The description adds nothing about parameter meaning, including the url parameter, which has no inline description and is only typed via a $ref. Baseline 3 is appropriate when the schema does the heavy lifting.

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?

States a specific verb and resource: 'Fetch or generate a normalized TikTok video transcript,' which immediately tells an agent what comes back (a transcript, not captions or video metadata). It does not explicitly distinguish itself from the near-identical siblings get_tiktok_video_transcripts (plural) or get_tiktok_video_captions, so the agent must infer the singular-vs-batch split from the name alone.

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 sentence 'A previously collected transcript can be reused' implies a caching path and hints that repeated calls are cheap in latency but not in cost, which is useful context for repeat requests. However, there is no explicit when-to-use guidance against the obvious alternatives (bulk get_tiktok_video_transcripts, or get_tiktok_video_captions for caption text), and no stated prerequisites such as a valid TikTok video URL.

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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