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Odile Formats: what it does and what it costs

get_catalog
Read-onlyIdempotent

The live price list and limits for Odile Formats, which reformats an existing video or photos for social platforms (it does not pick clips, write captions or edit). Call it first, before estimate_media_job or prepare_upload, to learn the preset and fit names, the file limits and the job flow. Needs no sign-in, takes no arguments and changes nothing. Returns { currency, packs[{id, credits, cents}], free_credits_per_account, credits_valid_months, buy_credits_at, purchasable_through_this_connection: true, how_to_buy, units, presets{video[], photos[]} (preset name strings), fits[] (fit name strings), limits{video_source_bytes, photo_source_bytes, max_source_photos, max_trim_seconds}, flow[] }. Prices are read from the same source the website charges from.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

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

Even though annotations already mark readOnlyHint=true, idempotentHint=true, and destructiveHint=false, the description adds meaningful behavioral context: no sign-in required, no arguments, no side effects, and prices are 'read from the same source the website charges from.' This goes well beyond the annotation defaults.

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

Conciseness5/5

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

The description is front-loaded with the core purpose and usage guidance, then provides the complete return shape because there is no output schema. Every sentence adds value: scoping, invocation ordering, side-effect disclosure, and the exact response fields.

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 zero-argument read-only catalog tool with no output schema, the description is remarkably complete: it states what the tool is for, when to call it, what it returns, and that it requires no authentication. It also names the sibling tools that should follow, so the agent can sequence its workflow correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With zero parameters, the schema provides no parameter documentation, but the description explicitly says the tool 'takes no arguments.' This matches the empty parameter list and gives the agent confidence that no input preparation is needed, satisfying the 0-parameter baseline.

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 opens with a specific verb and resource: 'The live price list and limits for Odile Formats,' and immediately scopes what Odile Formats does versus what it does not ('it does not pick clips, write captions or edit'). This clearly distinguishes get_catalog from the editing/job siblings.

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 gives explicit sequencing guidance: 'Call it first, before estimate_media_job or prepare_upload, to learn the preset and fit names, the file limits and the job flow.' It also states 'Needs no sign-in, takes no arguments and changes nothing,' which tells the agent exactly how to invoke it and what to expect.

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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