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dreamlayer_execution

Fetch the canonical state of an image generation execution to verify outcomes and resolve uncertain responses.

Instructions

Read canonical state for one execution. Use this after any uncertain response.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
execution_idYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.0

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 must convey behavioral traits itself. It states it 'reads' state, implying a non-mutating operation, which is the key trait. It also introduces 'canonical state,' which adds context on the nature of the data. However, it doesn't disclose additional details like error handling or side effects, which is acceptable given the tool's simplicity.

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 sentences with no fluff. The primary purpose is front-loaded first, followed by the usage instruction. Every word earns its place, demonstrating excellent conciseness.

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

Completeness3/5

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

For a tool with a single, self-explanatory parameter and no output schema, the description covers the when and what. However, it does not describe the return value or the nature of 'canonical state,' leaving some ambiguity for an agent deciding whether the response will answer its uncertainty. While not essential, this gap prevents a higher score.

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

Parameters2/5

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

Schema description coverage is 0%, so the description must compensate for the lack of parameter documentation. The only parameter, execution_id, is not mentioned or elaborated in the description; it only appears implicitly as the target of the read. This fails to add meaning beyond the field name and basic schema constraints.

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 clearly states the action 'Read canonical state for one execution' – a specific verb and resource. It distinguishes itself from siblings like dreamlayer_generate or dreamlayer_upload_image by focusing on reading state rather than actions.

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?

It provides a clear trigger condition: 'Use this after any uncertain response.' This tells the agent exactly when to call it. However, it doesn't explicitly mention alternatives or when not to use, but the context is sufficient for a simple tool.

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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