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Order editing from a URL

barevalue_submit_url

Order AI podcast editing for an audio file at a public URL. This is the simplest way to order. The file is downloaded, edited (noise, levels, filler words, dead air), and returned with a transcript and show notes. Audio only, one file, up to 60 minutes. Returns an order_id; poll barevalue_status until status is "done". For a file that is not online yet, put it somewhere with a direct link first: cloud storage with a public or signed link works (S3, Google Cloud Storage, R2, Azure).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
api_keyNoBarevalue API key (bv_sk_...). Get one with barevalue_register. Omit when the connection already sends an Authorization: Bearer header.
file_urlYesDirect, publicly downloadable URL of the audio file (not a landing page)
host_namesNoOptional host names (max 5), used to label speakers
guest_namesNoOptional guest names (max 10)
episode_nameYesName of this episode
podcast_nameYesName of the podcast
episode_numberNoOptional episode number, digits only (e.g. "42"). Anything else is ignored.
idempotency_keyNoOptional UUID. Send the same value when retrying so the order is not created twice. Generated when omitted.
duration_minutesNoOptional audio length in minutes if known. The real length is measured after download.
special_instructionsNoOptional instructions for the editor, e.g. "Remove the sponsor read", "Keep the blooper at the end"

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / episode_number / description
      Previous value: -"Optional episode number (e.g. \"42\", \"S2E5\")"New value: +"Optional episode number, digits only (e.g. \"42\"). Anything else is ignored."
  2. First observed

TDQS

A4.4/5.0
Behavior5/5

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

Adds substantial behavior beyond the annotations (readOnlyHint=false, openWorldHint=true, destructiveHint=false): the file is downloaded, edited for noise, levels, filler words and dead air, and returned with transcript and show notes. It discloses hard limits (audio only, single file, 60 minutes) and the asynchronous contract (returns order_id, then poll status), which the structured fields do not convey.

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?

Front-loads the core purpose and the 60-minute/audio-only constraints before the workflow and the hosting workaround, so an agent gets the essentials first. It is slightly long, and the cloud-storage vendor list (S3, GCS, R2, Azure) is more detail than strictly needed, but every sentence carries actionable information.

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?

With no output schema, the description still tells the agent what comes back (order_id), how to track completion (poll barevalue_status until 'done'), what the deliverable contains (edited audio, transcript, show notes), and what input is acceptable (public direct link, audio, up to 60 minutes). Nothing needed to call it correctly is missing.

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 all 10 parameters are already documented in the schema; the baseline is 3. The description reinforces the key constraint that file_url must be a direct public link and not a landing page, but adds no syntax or format detail beyond what the schema already states for the other parameters.

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?

States a specific verb and resource: order AI podcast editing for an audio file at a public URL. It also scopes the input ('Audio only, one file, up to 60 minutes'), which lets an agent distinguish it from sibling utilities like barevalue_estimate, barevalue_status, or barevalue_validate without opening any schema.

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?

Gives clear context ('This is the simplest way to order') and handles the main edge case explicitly: for a file that is not online yet, host it with a public or signed link on S3/GCS/R2/Azure. It also prescribes the follow-up workflow (poll barevalue_status until 'done'). It stops short of naming when to prefer an alternative sibling such as barevalue_estimate for pricing before committing.

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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