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Immersive Commons

by com.immersivecommons

Floor 10 print-farm hardware specs (build volumes, materials)

ic_prints_bed_specs
Read-only

Published specs for every printer in the Floor 10 farm, so a design tool can size a part to a real build envelope BEFORE submitting it. Each row carries build_volume_mm {x,y,z}, the accepted materials, an operational status, a verified flag and a sources[] provenance list. HONESTY CONTRACT: any dimension the farm has not published is null, never a guess, and verified:false means at least one field is missing or unsourced — do NOT design against an unverified row. status is not a live telemetry reading (the web app receives no feed from the farm); 'unknown' is the honest default. Note the auto-slicer only handles PLA, single-quantity, .stl/.3mf/.obj — everything else routes to manual farm-manager review. Args: {}. Returns: { ok, count, printers, verified_count }. Required scope: prints:read (ft-member+).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnlyHint annotation, the description discloses null semantics, the meaning of `verified:false`, and that `status` is not live telemetry. This honesty contract is crucial for an agent making design decisions and goes well beyond what annotations provide.

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?

Every sentence adds value: purpose, data fields, trust contract, status caveat, slicer routing, args, return shape, and required scope. Despite its length, there is no fluff – each clause is necessary for safe usage.

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

Completeness5/5

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

For a no-parameter, read-only tool with no output schema, the description fully covers data semantics, provenance, verification, status meaning, slicer constraints, return values, and permission requirements. Nothing critical is missing.

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?

With zero parameters, the baseline is 4. The description compensates by documenting the return shape (`{ ok, count, printers, verified_count }`), making the tool's outputs predictable even without an output schema.

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 opens with 'Published specs for every printer in the Floor 10 farm' – a specific verb+resource combination. It further clarifies the design-time use case ('BEFORE submitting it'), which clearly separates it from print submission and management siblings.

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 explicitly states when to use the tool ('size a part to a real build envelope BEFORE submitting it') and provides routing context via the auto-slicer limitation. It does not name an alternative tool, but the intended phase is clear enough.

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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TDQS

A3.7/5.0
Disambiguation4/5

Most tools are clearly scoped to distinct actions (e.g., ic_hack_apply vs. ic_hack_register, ic_rooms_create vs. ic_rooms_join). A few pairs could confuse an agent: floor10_submit_highlight vs. floorcast_push both submit HighlightStories but to different queues, and ic_directory_search / ic_agent_directory_lookup / ic_admin_list_members overlap in searching members. Overall, the long descriptions help disambiguate, but the volume requires careful reading.

Naming Consistency3/5

The dominant pattern is ic_<domain>_<verb>_<object> (e.g., ic_admin_list_pending_events, ic_headsets_checkout), but there are notable deviations: floor10_* and floorcast_* prefixes break the ic_ convention, and a few tools use noun-style names (ic_health, ic_capabilities, ic_donations_total). Verb placement also varies (get_* vs *_get, e.g., ic_get_my_membership vs. ic_membership_set_profile). Still, most names are readable and predictable.

Tool Count1/5

175 tools is an extreme count for a single MCP server, far beyond the 50+ threshold that indicates an unwieldy surface. While the platform covers many domains (events, files, hackathon, headsets, prints, rooms, etc.), bundling everything into one server makes discovery and selection difficult. This would be better split into several narrowly-scoped servers.

Completeness4/5

The tool set covers nearly every lifecycle for each domain: CRUD for files/folders, full hackathon admissions and judging, headset lending with waivers and incidents, print farm submission and handoffs, and room coordination. Minor gaps exist: no delete for files/folders, no cancel for events, and some actions (like revoking a Z.ai key or tearing down a room) are explicitly left to human console use. Overall, the surface is remarkably comprehensive for the stated scope.

Resources