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farpy_quote

Create a locked quote for a frame sub-range. Does not spend.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
frame_endYesLast frame, inclusive.
upload_idYesUpload id from farpy_inspect.
frame_stepNoFrame step.
frame_startYesFirst frame, inclusive.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A3.8/5.0
Behavior3/5

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

With no annotations provided, the description carries the full burden and does disclose the important side-effect boundary: 'Does not spend.' It does not explain what 'locked' means behaviorally, such as whether the quote expires, reserves resources, or is immutable, leaving some uncertainty.

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 two short sentences with no filler. The primary purpose is front-loaded and the critical behavioral constraint, 'Does not spend,' is stated separately and clearly.

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?

For a relatively simple tool with a complete input schema and an output schema present, the description covers the essential purpose and safety-relevant behavior. It is slightly incomplete around what 'locked' means and when to prefer this over a spending operation, but not critically so.

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 schema already documents all four parameters. The description adds only the high-level 'frame sub-range' context and does not add deeper parameter semantics beyond what the schema already provides.

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 action: creating a 'locked quote' for a 'frame sub-range', which clearly names both verb and resource. It also distinguishes itself from siblings by noting it does not spend, which is especially relevant next to farpy_start.

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?

The description implies usage through the phrase 'Does not spend,' signaling that this is for quote-only operations rather than executing work. However, it does not explicitly state when to use this tool instead of farpy_start or farpy_download, nor does it name any alternatives.

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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TDQS

A3.7/5.0
Disambiguation5/5

Each tool targets a distinct phase of the rendering workflow: capabilities, upload, inspect, submit, status, download, receipt, and wallet. There is no overlap in purpose, making misselection unlikely.

Naming Consistency4/5

All tools share the farpy_ prefix and snake_case, but some use verb_noun (inspect_blend, submit_render) while others are noun-only (capabilities, receipt, wallet). This is a minor inconsistency but the pattern is still readable.

Tool Count5/5

Eight tools is well within the optimal range for a focused cloud rendering service, covering the full lifecycle without unnecessary bloat. Each tool earns its place.

Completeness4/5

The toolkit covers the entire render pipeline from upload to payment receipt, with no obvious dead ends. A cancel operation is the only notable gap, but it is not integral to the core workflow.

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