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gen_compile_texture_paint_evidence

Compile a no-spend evidence receipt for a Tripo texture-paint pass from task, import, and viewport JSON results. Solves the need to document zero-cost texture paint operations.

Instructions

Compile a no-spend evidence receipt for a Tripo texture-paint pass.

KB: see knowledge_base/31_GENERATIVE_CONTENT_PIPELINE.md#texture-paint-evidence Example: gen_compile_texture_paint_evidence(session_name="demo", texture_task_result_json="", import_result_json="")

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
session_nameNodefault
approval_noteNo
model_task_idNo
wait_result_jsonNo
import_result_jsonNo
prepare_result_jsonNo
viewport_evidence_jsonNo
texture_task_result_jsonNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description carries full responsibility for disclosing behavioral traits. It only mentions 'no-spend' (implying no credit consumption) but does not describe side effects, required permissions, or what the receipt contains. This is a significant gap for a tool that likely writes data.

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

Conciseness3/5

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

The description is short and includes a helpful example and KB reference, but it is not well-structured or front-loaded. The essential information (what it does) is present, but the example and KB reference are not formatted to maximize readability for an agent.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool has 8 parameters, no schema descriptions, no annotations, and only a partial example. The description does not explain the full parameter set, usage context, or return value (though an output schema exists). It is inadequate for an agent to call correctly without additional knowledge.

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

Parameters1/5

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

Schema coverage is 0%, so the description must compensate, but it only provides an example with three parameters (session_name, texture_task_result_json, import_result_json). The remaining five parameters (approval_note, model_task_id, wait_result_json, prepare_result_json, viewport_evidence_json) are entirely unexplained, leaving agents unable to populate them correctly.

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?

The description states a specific verb (compile) and resource (evidence receipt for a Tripo texture-paint pass), making the tool's purpose clear. It does not explicitly differentiate from sibling tools like gen_compile_generated_animation_evidence, but the texture-paint specificity is sufficient to distinguish it.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is given on when to use this tool versus alternatives such as gen_record_texture_paint_pass or gen_capture_texture_paint_snapshot. The description implies it is for post-pass evidence compilation but provides no exclusions or alternative 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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