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Nudge Model Pitch Down

nudge_model_pitch_down

Decrease the pitch rotation of a 3D model along the X axis by a specified number of degrees. The tool queries current state before adjusting to maintain accuracy during manual interactions.

Instructions

Adjust the model pitch (X axis rotation) downward relative to current rotation. This tool automatically queries fresh state before performing the adjustment to ensure accuracy, even if the user has manually interacted with the model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
degreesNoAmount to decrease pitch in degrees (defaults to 5°)
Behavior4/5

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

With no annotations provided, the description carries full burden and does well by disclosing key behavioral traits: it's a mutation tool (adjusts pitch), it queries fresh state before adjustment for accuracy, and it works even if the user has manually interacted with the model. This covers important operational context beyond basic functionality.

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 perfectly concise with two sentences that each earn their place: the first states the core purpose, the second adds crucial behavioral context about state querying. It's front-loaded with the main action and wastes no words.

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 single-parameter mutation tool with no annotations and no output schema, the description does well by explaining what the tool does, how it behaves (queries fresh state), and when it's appropriate. However, it doesn't mention what happens on success/failure or return values, which would be helpful given the lack of output schema.

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

Parameters3/5

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

The schema description coverage is 100%, so the schema already fully documents the 'degrees' parameter. The description doesn't add any additional parameter semantics beyond what's in the schema, so it meets the baseline of 3 where the schema does the heavy lifting.

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 specific action ('Adjust the model pitch downward'), identifies the resource ('model pitch'), and distinguishes it from siblings like 'nudge_model_pitch_up' by specifying the direction. It provides a precise verb+resource combination that leaves no ambiguity about the tool's function.

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?

The description explicitly states when to use this tool ('to adjust the model pitch downward relative to current rotation') and mentions it queries fresh state for accuracy, which provides clear context. However, it doesn't explicitly mention when NOT to use it or name specific alternatives like 'nudge_model_pitch_up' or 'set_model_rotation' for different scenarios.

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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