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by io.github.treza-labs
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Copy a reference style

copy_reference_style

"Make it like this video": read a reference short the account has (a music edit: titles over a beat) and save a pipeline that makes more like it. Its cuts, the music's tempo and drop, and how they line up are measured; its hook, titles, top bar, music genre and picture look are read by a model. The result is a draft Beat Edit Short pipeline cutting the same beats a shot, with the music brief at the reference's tempo and drop and the writer told its style; copied and couldNotCopy say what carried over. Takes about a minute and a few cents, waited on in this call; nothing renders. Then estimate_run_cost and run_pipeline with the person's topic on the brief input. The video must be in the library (import_media); YouTube links cannot be fetched. Needs the pipelines:run and pipelines:write scopes.

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": {
      "sourceUrl": "<sourceUrl>"
    },
    "name": "copy_reference_style"
  }
}

Input Schema

NameRequiredDescriptionDefault
nameNoWhat to call the pipeline.
topicNoWhat the first video should be about. Defaults to the reference's own topic.
sourceUrlYesThe reference video, from list_assets.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Beyond the annotations it discloses cost and latency ("about a minute and a few cents, waited on in this call"), that nothing renders, that the output is a draft rather than a published pipeline, what `copied`/`couldNotCopy` report, and the required pipelines:run and pipelines:write scopes. These are exactly the operational facts an agent needs before calling a non-idempotent write tool.

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

Conciseness3/5

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

The relational opening is effective and front-loaded, and every sentence carries information. But the body is a dense wall of run-on sentences with compressed jargon ("cutting the same beats a shot") and the prerequisites/scopes are buried at the end, which costs readability.

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

Completeness5/5

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

For a costly, minutes-long, non-idempotent write operation, the description covers prerequisites, duration, price, what is and is not produced, scopes, and the follow-up call sequence. No output schema exists, yet the `copied`/`couldNotCopy` result is described, leaving nothing essential unexplained.

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 100%, so the baseline is 3; the description adds that the source video must come from the library, reinforcing `sourceUrl`. However it references the pipeline's `brief` input rather than clarifying the `topic` and `name` parameters, so it adds little new meaning over the schema.

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 uses a concrete verb-and-resource framing ("read a reference short ... and save a pipeline that makes more like it") and names the exact artifact produced — a draft Beat Edit Short pipeline. It clearly separates this from siblings like create_pipeline or create_editor_project by describing analysis of cuts, tempo, drop, hook, titles and look.

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

Usage Guidelines5/5

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

It states when and how to use it ("Then estimate_run_cost and run_pipeline with the person's topic on the `brief` input") and an explicit exclusion: the video must already be in the library via import_media, and YouTube links cannot be fetched. That is an unambiguous when-to-use and when-not-to-use rule.

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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