Hook Detector

optimize_video

New packages (4, 8 or 12) for your published video: the original scored first against the real outliers on its subject, then each new package (title, thumbnail with every word checked, what it tests) scored the same way, best first, with vs_original. 10 credits a delivered package. Answers at once; read it with get_optimize. Same as POST /v1/optimize.

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": {
      "video_url": "<video_url>"
    },
    "name": "optimize_video"
  }
}

Input Schema

Name	Required	Description
`size`	No
`count`	No
`run_id`	No
`api_key`	No
`video_url`	Yes
`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 26, 2026

TDQS

C2.8/5.0

Behavior3/5

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

With no annotations, the description carries the full burden, and it does disclose two valuable traits: cost ('10 credits a delivered package') and that results are read back via get_optimize. It does not state auth requirements, whether anything is published or overwritten, or what happens on the original video/thumbnail beyond scoring.

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

Conciseness2/5

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

It is a single garbled run-on paragraph with fragmented clauses ('scored the same way, best first, with vs_original') that cost the agent parsing effort. It is not bloated, but the structure is poor and the key information (cost, follow-up tool) is buried mid-sentence.

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 needn't be explained, and the description correctly points to get_optimize for retrieval. However, for a 6-param tool with low schema coverage, it leaves key gaps (what `size` means, run_id semantics) that an agent would need before calling correctly.

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 coverage is only 17% (just idempotency_key), so the description must compensate. It helps somewhat by naming package counts ('4, 8 or 12'), which maps to an undocumented parameter, but it never explains `size`, `run_id`, `api_key`, or ties the numbers explicitly to `count`. Most parameters remain unexplained in both places.

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

Purpose3/5

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

The description conveys that the tool produces new title/thumbnail packages for a published video and scores them against outliers ('best first, with vs_original'). The verb is only implied ('New packages...'), and the prose is broken enough ('best first, with vs_original') that an agent must work to extract the actual action. It does at least distinguish itself from siblings like score_package or get_optimize.

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?

It gives one concrete workflow cue: 'Answers at once; read it with get_optimize,' naming the follow-up tool. It does not say when to use this vs score_package, preview_package, or make_thumbnails, nor any prerequisites. Usage is implied rather than stated.

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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