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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 Pro (google-gemini-3-image) 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

TableJSON 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

A4/5.0
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 meaningful behavior beyond the schema: the proposal is saved for user review, the returned proposalMarkdown must be shown inline, the agent must wait for Accept/Decline, and reviewUrl must never be auto-opened. It omits permissions, failure modes, and what happens on decline, keeping it short of 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?

Front-loaded with purpose, then requirements, then display behavior, in a logical order. It is long and somewhat dense with formatting rules, but nearly every sentence carries actionable guidance, with only mild redundancy around the model-ID versus friendly-name rule.

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?

There is no output schema, but the description compensates by explaining what is returned (proposalMarkdown, reviewUrl) and how to handle it, plus the full content contract. What remains thin is edge-case behavior (errors, decline path), which is reasonable to omit here.

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 genuinely extends proposalMarkdown semantics — mandatory sections, enumerated shots rather than file references, and the rule to keep raw model IDs in arguments while using friendly names in user text. That is real added meaning beyond the schema string.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (Save) and resource (a proposal document) and adds scope ("for user review before implementing a complex project"). It does not explicitly differentiate itself from close siblings like update_proposal, get_proposal, set_proposal_status, or save_experience_game_proposal, so an agent must infer the boundary from context.

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 usage context — call this before implementing a complex project — and spells out required proposal content (Models section, cost section, numbered scene/beat list). It stops short of naming alternatives or stating when not to use it (e.g., versus update_proposal), so it lacks explicit routing.

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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