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Anchor the scene to metres

scene_anchor

Calibrate a scan by defining two world points and their real distance in meters to unlock metric measurements for navigation and export.

Instructions

Metric-anchor calibration (POST /anchor): two picked world points + their real distance in metres. Non-destructive (writes NEW derived/anchor/* artifacts + the derived_latest pointer) and it is what unlocks units:"m" for measure/nav/export. materialize:"job" returns 202 with a job_id to poll via workspace_job_wait.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
point_aYes
point_bYes
scan_idYes
distance_mYes
materializeNojob
Install Server

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states the operation is non-destructive, writes new derived artifacts and updates a pointer, and describes the async job behavior with 202 and job_id polling. This is strong transparency.

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?

Three sentences deliver the core purpose, side effects, and async response behavior without redundancy. The most important information is front-loaded and every sentence adds value.

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?

The description covers purpose, side effects, and the default async response, which is enough for typical invocation. It does not mention the behavior of the 'sync' materialize option or the exact return shape beyond job_id, so there is a small completeness gap given no output schema exists.

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 description coverage is 0%, so the description must add meaning beyond bare parameter names. It explains point_a and point_b as picked world points, distance_m as real distance in metres, and materialize:'job' behavior. However, scan_id is not mentioned and the sync variant is not explained, leaving some burden unaddressed.

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 states a specific operation: metric-anchor calibration with two world points and a real distance in metres. It clearly names the endpoint and explains the purpose (unlocking 'm' units), which distinguishes it from measurement siblings like scene_measure_distance.

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 conveys when to use the tool: it is the calibration step that unlocks metric units for measure, navigation, and export. It does not explicitly name alternatives or exclusions, but the context around units and siblings makes the intended usage clear.

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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