Hook Detector

review_video

Video Review of any public long video (15 credits): five ranked fixes with times and the counted fact behind each, six sub-scores each with what it is computed from, the hook scored and rewritten (labelled as written), the curve (YouTube's replay peaks, not retention; your Studio curve via graph_points; else predicted, not measured), the story with gap rules, pace and loudness per section, the next five uploads. Runs as a job: answers the paid call (pending); get_call reads it. Same as POST /v1/review.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "review_video"
  }
}

Input Schema

Name	Required	Description
`url`	No	a YouTube link: watch, youtu.be or shorts address
`api_key`	No
`graph_points`	No	your real curve from read_retention_graph
`idempotency_key`	No	1 to 255 visible ASCII characters; the same key and request within 24 hours answer the saved remix and charge nothing; the same key with another request is 422 idempotency_key_reused

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

AddedOct 27, 2026

TDQS

A4.1/5.0

Behavior4/5

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

With no annotations, the description carries full burden and does well: it discloses the credit cost (15 credits), the asynchronous job execution (pending → get_call), and the caveats around curve computation (YouTube's replay peaks vs. retention, Studio curve via graph_points, else predicted). It doesn't mention auth or error handling, but for a public video review tool that's a minor gap.

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 dense but front-loaded with the core purpose and outputs. It could benefit from bullet points for readability, but every sentence earns its place by conveying essential details about outputs, cost, and job flow.

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 (comprehensive video review with many outputs), the description provides sufficient context: what the results contain, the cost, the async job mechanism, and how to retrieve results via get_call. An output schema exists, so return value details are covered elsewhere. A minor gap is the unclear requirement for the url parameter despite zero required params in the schema.

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 75%, so baseline is 3. The description adds meaning for graph_points by explaining its role (Studio curve via graph_points) and the default behavior (predicted curve). It also references idempotency indirectly via 'Same as POST /v1/review' and the schema description is detailed. However, it doesn't clarify the api_key parameter or the url parameter beyond 'any public long video'.

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 states a specific verb+resource ('Video Review of any public long video') and enumerates the concrete outputs (five ranked fixes, six sub-scores, hook rewrite, curve, story, pace/loudness, next five uploads). It distinguishes from siblings like review_short by explicitly specifying 'long video' and from other review tools by listing comprehensive outputs.

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

Usage Guidelines4/5

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

It implies usage for full long-video reviews and clarifies the async job pattern ('Runs as a job: answers the paid call (pending); get_call reads it'). It doesn't explicitly state when to prefer this over other review tools (e.g., review_short, review_hook), but the scope is clear enough that an agent can infer appropriate use.

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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