VoxelDraft – AI Voxel Modeling

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

Annotations already state readOnlyHint=true, destructiveHint=false, and openWorldHint=false. The description adds important behavioral context beyond those annotations: this is a stateless computation that returns an opaque handle and does not save to an account. It still does not discuss rate limits or auth, but the key non-persistence behavior is disclosed.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately front-loaded with purpose and the stateless behavior, then provides the command DSL needed to invoke the tool. It is long, but the command list earns its place. One sentence about token savings is somewhat redundant with the earlier instruction-stream rationale.

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

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

For a tool with no output schema and sparse annotations, the description gives enough syntax and behavioral context to invoke it correctly, including the command DSL and the fact that it returns an opaque handle. It could be more complete by routing between related creation, editing, saving, and rendering tools.

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

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

Schema description coverage is 0%, so the description carries the burden. It thoroughly documents the commands parameter, including command forms, coordinate ranges, and color formats, which is the difficult part of the schema. It does not explain the name or palette parameters in comparable detail, but it compensates well overall.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: create an editable VoxelDraft model from a compact instruction stream. It also clarifies the output (opaque model handle) and explicitly distinguishes this from persistence by saying it does not save anything to an account.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives clear internal guidance to prefer the compact instruction stream over raw voxel JSON, but it does not explicitly say when to use this tool versus sibling tools like edit_voxel_model, load_voxel_project, or save_voxel_model. The use case is implied rather than routed.

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

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

Annotations declare readOnlyHint=true and destructiveHint=false, and the description reinforces this by explaining the operation is stateless and leaves saved cloud projects untouched, which is valuable because 'appending commands' could otherwise read as a mutation. It also discloses hard constraints (integer coordinates 0..63, colors as #RRGGBB or palette index) that annotations do not cover, though it says nothing about error behavior or whether command order matters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads purpose, statelessness, and the key 'don't emit raw voxel JSON' advice before the grammar reference, which is dense but each command entry carries unique syntax the agent cannot infer. It is long, but the length is justified by the opaque command DSL; little is wasted.

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

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

There is no output schema, and the description covers the return conceptually ('compute a new model handle'), the full command grammar, and the coordinate/color conventions. It omits a few details an agent might want, such as whether commands apply sequentially, how errors in a command list are reported, or whether the returned handle feeds into other tools.

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

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

Schema description coverage is only 33% (only 'model' is documented), so the description must compensate and largely does: it fully specifies the command tuple grammar for all twelve command types, coordinate range, and color encoding. The 'palette' parameter is never named explicitly, though the 'zero-based palette index' color rule implies its role, leaving a small gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('compute a new model handle'), resource (VoxelDraft model handle), and mechanism ('appending compact modeling commands'). The explicit note that it is stateless and does not modify a saved cloud project distinguishes it from siblings like save_voxel_model and create_voxel_model without opening their schemas.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives a clear directive to use the compact instruction stream rather than one JSON object per voxel, plus selection guidance among command types (box/roof/ellipsoid/cylinder for bulk, runs for irregular silhouettes, repeat/mirror for symmetry, points only for small details). It does not explicitly state when to choose this tool over load_voxel_project or create_voxel_model, so it stops short of full alternative routing.

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

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

Annotations already declare readOnly/destructive/openWorld, but the description adds real value beyond them: it clarifies the tool returns download URLs rather than model bytes, that exporting does not modify saved data, and that OBJ output reuses vertices and drops hidden internal faces (an optimization/wire-size trait).

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two dense sentences, front-loaded with the core action and output, then the read-only guarantee. No filler or restatement of the name.

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

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

With no output schema, the description usefully discloses that the return is download URLs, which is the key thing an agent needs. Remaining gaps are minor: no explanation of the 'model' identifier (ID vs name) and no note on URL expiry or size limits.

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

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

Schema description coverage is 0%, so the description must compensate. It meaningfully characterizes the format options ('optimized OBJ+MTL' vs 'compact VoxelDraft JSON'), but the required 'model' parameter is left entirely unexplained in both schema and description.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb and resource ('Compute direct download URLs' for a voxel model export) and names the two output formats. It distinguishes itself implicitly from save/load siblings by framing the result as download URLs rather than persisted files, though it never names a sibling explicitly.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

There is no when-to-use guidance and no comparison to alternatives such as save_voxel_model or render_voxel_model. The only inferable guidance is the format choice, which is a parameter concern rather than usage context.

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

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is fully covered by structured fields. The description adds one useful behavioral fact — the response is a summary, not the raw voxel array — but says nothing about error cases, handle invalidation, or size limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, no filler, and the scope-defining clause about the voxel array is front-loaded where it matters most. Every clause earns its place.

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

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

With no output schema, the description correctly compensates by enumerating the returned fields, and the read-only nature is fully covered by annotations. Only the origin/format of the model handle is left unspecified, a minor gap for a one-parameter tool.

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

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

Schema description coverage is 0%, so the description must carry the load for the single 'model' parameter. It partially does by calling it a 'VoxelDraft model handle', hinting at the expected token type, but gives no format, origin (e.g., from create_voxel_model or load_voxel_project), or validity rules.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Inspect') and resource ('a VoxelDraft model handle') and enumerates exactly what it returns: voxel count, command count, bounds, and colors. The closing clause 'without dumping the full voxel array' separates it from data-heavy siblings like render_voxel_model and export_voxel_model.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'without dumping the full voxel array' implies this is the lightweight summarization path, but it never states when to prefer it over siblings such as render_voxel_model, export_voxel_model, or edit_voxel_model. Usage is inferable rather than explicit.

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

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

Annotations already declare a safe read (readOnlyHint=true, destructiveHint=false), so the bar is lower, yet the description adds genuinely useful context: it discloses what is NOT returned (full voxel data) and states the required VoxelDraft project-read OAuth scope. That auth/return-shape disclosure goes beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences with zero waste, front-loading the core action and resource before the scope qualifier. Every clause earns its place.

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

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

With no output schema, the description partly compensates by noting that project listings exclude full voxel data, and it names the required OAuth scope. For a zero-parameter read tool this is close to complete, though the exact shape of the returned project list is not described.

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

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

The tool takes zero parameters, so there are no parameter semantics to document and the baseline is 4. The description appropriately adds no parameter detail because none exists.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb (List) and resource (the signed-in user's private VoxelDraft Cloud Projects), which is a distinct resource from the model-oriented siblings. It does not explicitly name a sibling it is distinct from, but the project-level scope is self-evidently different from model create/edit/render operations.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'without returning full voxel data' implies this is the metadata-only listing step before inspecting or loading a project, but it never states when to choose this over load_voxel_project or inspect_voxel_model. Usage is only implied, not explicit.

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

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

Annotations already declare the safety profile (readOnlyHint, destructiveHint=false), and the description adds non-annotation context: the OAuth project-read scope requirement and the non-destructive nature ('Loading does not modify the saved project') plus the return shape. The auth requirement is genuinely valuable behavioral disclosure.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short sentences, front-loaded with the action and scope constraints, and no filler. Slightly more could be trimmed but it is efficient.

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

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

For a simple read tool with no output schema and rich annotations, it adequately covers the scope requirement, non-modification, and return form. However, the language parameter is left entirely unexplained, leaving a real gap an agent must guess at.

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

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

Schema description coverage is 0%, so the description must carry parameter meaning, yet it never explains projectId or the language enum (which appears to control localization). With two undocumented parameters, the description does not compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb ('Retrieve') and resource ('one private VoxelDraft Cloud Project') and the output form ('compact MCP model handle'), which implicitly separates it from the plural list_voxel_projects. It is clear but never names a sibling to sharpen the contrast between loading versus listing or inspecting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It supplies one precondition (the project-read OAuth scope) and hints at why to load rather than fetch raw data ('preserving token efficiency'), but gives no explicit when-to-use/when-not guidance against siblings like inspect_voxel_model or list_voxel_projects. Usage must be inferred.

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

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

Goes well beyond the readOnly/destructive/openWorld annotations by disclosing tier gating (Plus users), credit consumption, rate limiting, the dual output modes (always a WebGL URL, conditionally a cached PNG), and explicitly that saving state is untouched. This is exactly the behavioral context an agent needs before invoking.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences, front-loaded with the core action before the conditional Plus/PNG caveat and the non-mutation guarantee. No filler or redundancy.

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

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

There is no output schema, so the description must carry weight, and it partially does by describing the two return paths (URL and optional PNG). But with 6 undocumented parameters and no return-shape detail beyond what the image is, it is only adequate for a tool of this complexity.

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

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

Schema description coverage is 0% across 6 parameters, so the description carries the full burden — yet it only explains includeImage. The meaning of model (ID, path, or inline data), view, imageSize, background, and language is left entirely unstated despite four of them being enums.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb+resource ('Preview a voxel model') and names the platform, so an agent knows this is a read-only preview operation. It implicitly contrasts with mutation siblings via 'does not modify a saved user project,' but never names export_voxel_model or inspect_voxel_model, which an agent might also consider for viewing a model.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives conditional context for includeImage (Plus users only, credits, rate limits), which implies when the PNG path is available. However, there is no guidance on when to choose this tool over export_voxel_model or inspect_voxel_model for similar-looking tasks.

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

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

Annotations already declare destructiveHint=true, readOnlyHint=false and openWorldHint=false, so the safety profile is covered. The description adds genuinely new context: it names the required OAuth scope (project-write) and spells out that supplying projectId overwrites an existing owned project. It does not cover failure behavior, but it does more than restate the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Three tight sentences with no filler, and the core action plus destination is front-loaded. The prerequisite scope sentence is slightly interleaved but still earns its place.

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

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

For a two-parameter mutation tool with no output schema, the definition covers the essentials: destination, required scope, and overwrite semantics. What is missing is the nature/format of the required 'model' payload and any indication of what success or failure returns, which keeps it out of the top tier.

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

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

Schema coverage is 0%, so neither parameter is documented in the schema. The description compensates for projectId by explaining its create-vs-overwrite semantics, but 'model' is left entirely undefined — no format, type, or size expectations. Partial compensation puts this at the minimum-viable level.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource ('Save a model to ... VoxelDraft Cloud Projects') and names the destination scope, which separates it from local-model siblings like create_voxel_model or edit_voxel_model. It stops short of explicitly contrasting itself with any named alternative, so it lands just below the top tier.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives a conditional usage rule for one path: 'Pass projectId to update and overwrite an existing owned cloud project.' That tells the agent how to choose between creating a new cloud project and overwriting one, but there is no guidance on when to use this tool versus edit_voxel_model or create_voxel_model.

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