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save_proposal

Save a proposal document for user review before implementing a complex project. The proposal MUST include a Models section listing the friendly names of the planned image/still and video models, a "💰 Estimated Cost" section, and a concrete numbered scene/shot or beat list. Default project models are Nano Banana 2.1 (google-nano-banana-2-1) for character/location/shot still images and Gemini Omni 1.1 Flash (google-gemini-omni-1-1) for videos after still-image approval. Keep those raw IDs in tool arguments and use friendly model names in user-facing proposal text. Do not use source-file references such as "from script.md" or vague language such as "approximately X shots" instead of enumerating the planned work. Display the returned proposalMarkdown inline in chat and wait for the user to use the inline Accept or Decline controls. The reviewUrl is secondary and must never be opened automatically. Do not respond with only a link or a relative URL.

Input Schema

NameRequiredDescriptionDefault
editIdYesThe edit ID to save the proposal to
threadIdNoOptional chat thread ID
sourceMediaNoUploaded media from the original Spark request that must remain available after proposal approval
workspaceIdYesThe workspace ID
proposalMarkdownYesThe full proposal content in Markdown format, including concrete numbered scenes/shots or beats. If based on a script or beat sheet, extract and enumerate the planned shots; do not merely reference the file.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does disclose real behavior beyond the schema: the inline Accept/Decline review flow, that reviewUrl is secondary and must never be auto-opened, and that proposalMarkdown must be displayed inline. It omits mutation semantics (does it overwrite an existing proposal?), permission/auth requirements, and failure behavior, keeping it from a 5.

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?

Purpose and the review flow are front-loaded, and each sentence carries a rule an agent must obey. The paragraph is dense and long, but almost nothing is redundant, so it avoids a lower score without being a model of brevity.

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 5-parameter write tool with no output schema and no annotations, the description covers the required proposal content, default models, and the full human review loop, and even names the returned proposalMarkdown. It leaves the overwrite/update relationship with update_proposal and any error handling unaddressed.

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?

Schema coverage is 100%, so the baseline is 3, but the description adds genuine meaning: it specifies the raw model IDs that belong in tool arguments versus the friendly names that belong in proposalMarkdown, which is exactly the kind of argument-level nuance the schema does not encode. It says nothing extra about editId, threadId, or sourceMedia.

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+resource ('Save a proposal document') and its trigger condition ('for user review before implementing a complex project'), which cleanly separates it from get_proposal, update_proposal, and the various save_*_proposal siblings.

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 strong when-to-use context (before implementing a complex project) plus content prerequisites and explicit anti-patterns ('Do not use source-file references', 'vague language such as approximately X shots'). It does not, however, name an alternative tool or state when not to save a proposal, so it stops short of a 5.

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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