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FabTally 3D-Print Slicer, Quote & DFM

by com.fabtally

Scale advisor (fit-bed / dimension / percent)

scale_advisor

FREE. Report the new dimensions / time / filament / cost after scaling a model. target: 'fit-bed' (largest uniform scale that fits the printer), 'percent:' (e.g. percent:150), or 'dim::' (e.g. dim:z:80). Paste a link: Thingiverse/Printables/MakerWorld model pages, a GitHub blob, Google Drive or Dropbox share link, a direct .stl/.3mf/.obj/.ply/.step URL, or a .zip (first printable model inside is used). Local file? Upload once at https://fabtally.com/upload and paste that URL. Dimensions are exact; time/filament are estimated from the volume factor off one real slice. Fair-use limited.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
marginNoBYO pricing: fractional margin, 0.3 = 30%.
targetYes'fit-bed' | 'percent:<n>' | 'dim:<axis>:<mm>' (axis x|y|z).
printerNoPrinter id from list_printers (elegoo-neptune4-max, bambu-a1, bambu-a1-mini, bambu-p1s, bambu-x1c, prusa-mk4, prusa-mini, ender3-v3, creality-k1, creality-k1-max, voron-24-350, anycubic-kobra2). Default elegoo-neptune4-max.
qualityNoQuality preset: draft 0.28mm | standard 0.20mm | fine 0.12mm layer height.
currencyNoBYO pricing: currency code (USD, EUR, ...). Default USD.
filenameNoFile name incl. extension, e.g. 'bracket.stl'. Required with model_base64.
materialNoFilament/material id (pla, pla-cf, petg, petg-cf, abs, abs-cf, asa, asa-cf, nylon, pc, pet, tpu). Default pla.
quantityNoNumber of parts (1-10000). Volume discounts apply. Default 1.
model_urlNoPREFERRED. Public URL to the 3D model. Paste a link: Thingiverse/Printables/MakerWorld model pages, a GitHub blob, Google Drive or Dropbox share link, a direct .stl/.3mf/.obj/.ply/.step URL, or a .zip (first printable model inside is used). Local file? Upload once at https://fabtally.com/upload and paste that URL. The server fetches and (if a zip) unpacks it.
setup_feeNoBYO pricing: flat per-job setup fee.
model_base64NoBase64 model bytes — small-file fallback only (roughly <50KB). MCP clients (Claude/ChatGPT Desktop) truncate large inline tool arguments, so a real STL can silently arrive corrupted. For anything bigger use model_url (upload at https://fabtally.com/upload first). Provide `filename` too.
minimum_priceNoBYO pricing: per-unit price floor.
infill_percentNoSparse infill density percent (0-100).
markup_percentNoBYO pricing: extra % markup on top of margin.
material_cost_per_kgNoBYO pricing: override material $/kg.
machine_rate_per_hourNoBYO pricing: machine time cost/hour.

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the transparency burden, and it does well: it states the service is 'FREE,' warns of 'fair-use limited,' clarifies that 'dimensions are exact; time/filament are estimated from the volume factor off one real slice,' and explains that zips use the first printable model and that the server fetches/unpacks links.

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 front-loaded with the core purpose and target syntax, then proceeds to input methods and caveats. It is somewhat long and repeats model_url details already present in the schema, but each sentence adds useful operational context or clarity.

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?

Given 16 parameters, no annotations, and no output schema, the description provides adequate operational context: what it reports, how to specify targets, how to supply models, estimation caveats, and fair-use limits. It could mention more about expected output structure, but the description covers the key usage scenarios.

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 coverage is 100%, so baseline is 3, but the description adds meaningful value by explaining 'fit-bed' as 'largest uniform scale that fits the printer' and giving concrete examples like 'percent:150' and 'dim:z:80.' It also reinforces model_url semantics with supported link types.

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 a specific verb+resource: 'Report the new dimensions / time / filament / cost after scaling a model.' It precisely defines the three target modes (fit-bed, percent, dim) and clearly distinguishes this tool from siblings like slice_model or whatif_infill by focusing on scaling outcomes.

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 gives clear context for when to use the tool: any time a user needs scaled dimensions/cost estimates. It also covers input methods (paste link, local upload, zip handling) and target syntax, though it does not explicitly name sibling tools as alternatives or state when not to use it.

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

A3.9/5.0
Disambiguation2/5

Four tools—analyze_model, analyze_3d_model, check_printability, and validate_model—perform overlapping geometry analysis with printability verdicts, making it hard to tell which to call. The detailed descriptions help, but the boundaries are subtle (general vs printing-specific, full vs fast), and an agent could easily pick the wrong one.

Naming Consistency4/5

Most names follow a clear verb_noun snake_case pattern (e.g., list_printers, slice_model, get_print_quote). Minor deviations like analyze_3d_model, cost_breakdown, scale_advisor, and whatif_infill are still readable and do not break the overall consistency.

Tool Count4/5

With 14 tools, the count is well within the 3–15 range for a specialist service and each tool addresses a distinct stage of the quoting/DFM workflow. The count feels slightly inflated by the near-duplicate analysis cluster, but it is not excessive for the domain.

Completeness4/5

The tool surface covers the full lifecycle: model analysis, printability checks, slicing, quoting, cost breakdown, printer comparison, orientation optimization, material/settings recommendations, and scaling. Minor gaps exist (e.g., no batch processing or material-specific parameter tuning), but agents can compose the existing tools to achieve most workflows.

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