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validate_scene_interpretation_plan

Validates a persisted AI scene plan against current immutable evidence to confirm the plan aligns with source data.

Instructions

Validate a persisted AI scene plan against current immutable evidence.

Input Schema

NameRequiredDescriptionDefault
planYes
graph_pathYes
visual_manifest_pathYes

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.8.0

TDQS

C2.7/5.0
Behavior2/5

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

No annotations are provided, so the description must carry the full behavioral burden. It implies a read-only validation against immutable evidence but does not state whether the plan or evidence are altered, what permissions are required, or what failure modes exist. With output schema present, return values need not be explained, but core behavioral traits remain undisclosed.

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?

The description is a single, front-loaded sentence with no wasted words. The term 'immutable evidence' is slightly jargon-heavy but still conveys the core constraint efficiently.

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?

Given three required parameters, an entirely undocumented schema, and a nested plan object, the one-sentence description is insufficient for an agent to call the tool correctly. The output schema helps with return values, but input expectations (path formats, plan structure) are missing.

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% across three required parameters, including a nested 'plan' object. The description vaguely maps 'persisted plan' to the plan parameter and 'evidence' to the path parameters, but gives no format, structure, or path expectations. It does not compensate for the schema's lack of description.

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 ('validate') and resource ('persisted AI scene plan against current immutable evidence'), making it distinguishable from the sibling create_scene_interpretation_plan. It does not explicitly name alternatives, but the action and object are clear enough for an agent to identify the tool's role.

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?

There is no guidance on when to use this tool versus alternatives like create_scene_interpretation_plan or validate_decision_pack. The phrase 'validate a persisted plan' implies usage, but no conditions, prerequisites, or exclusions are stated.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.