Extrabold Tools Gridfinity

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

Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered. The description adds only that the URL is 'shareable' and derived from exact settings; it does not say whether anything is uploaded or persisted, whether the URL is stateless, or how it round-trips settings. Adequate but thin given the annotation coverage.

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 short sentences, front-loaded with the core action and followed by a routing cue, with no filler. It is appropriately sized, though the second sentence spends its budget on only one alternative rather than the most relevant one.

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?

A 41-parameter, nested-object tool with no output schema and 10% schema coverage needs far more explanation of inputs and of what the produced URL contains. The description omits parameter guidance entirely and does not state the return value (a URL string) or its relationship to the sibling generator 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?

With 41 parameters at only 10% schema description coverage, the description must carry the explanatory burden, and it does not: it says only 'exact baseplate settings' without explaining any parameter groups, units, or the printer/tolerance implications. The phrase 'exact settings' does hint at full-fidelity round-tripping, which is marginally useful, but the vast parameter surface is undocumented in both places.

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 (create a shareable Gridfinity baseplate URL) and the input basis (exact baseplate settings), which is clearly distinct from a generator that outputs geometry. It names one sibling and the condition for it, but oddly routes to generate_gridfinity_grid rather than the more closely related generate_gridfinity_baseplate, leaving some ambiguity about which generating tool this URL complements.

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?

Provides one explicit routing rule: use generate_gridfinity_grid when the user asks for a grid by rows and columns. However, it never clarifies when to prefer this URL tool over generate_gridfinity_baseplate, which presumably consumes the same settings, so the primary selection decision is left 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?

Annotations already declare readOnlyHint=true, destructiveHint=false, idempotentHint=true, and openWorldHint=false, so the safety profile is covered. The description adds scoping context ('usable' presets, 'exact' models), but does not describe filtering behavior, result limits, or pagination.

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?

A single front-loaded sentence enumerates scope and search fields with no filler. 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?

For a simple read-only search tool with annotations covering safety and no output schema, the description is nearly complete: it names the resource and all search dimensions. The only gap is that limit/pagination behavior is not mentioned, which is a minor omission.

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 exactly 50%: the query field is well documented in the schema, and the description repeats essentially the same searchable fields without adding syntax or format details. The limit parameter is undocumented in both schema description and tool description, leaving its behavior (max 20, default 10) unexplained beyond the raw JSON constraints.

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 (Find) and resource (drawer presets, Eurobox/KLT models) with the searchable fields enumerated. The distinction from sibling generate_* tools is clear from the verb, though no alternative is named 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?

The description explains what can be searched, but gives no guidance on when to use this tool instead of find_gridfinity_printers or the generate_* siblings. No prerequisites, exclusions, or alternative-selection context are provided.

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 this a safe, idempotent, closed-world read, so the safety profile is covered. The description adds real behavioral value beyond that: what comes back ('exact model IDs and printerBuildVolume objects') and the disambiguation rule for ambiguous matches. It says nothing about the limit/pagination behavior of a capped lookup.

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 with zero filler, front-loaded with the lookup action before the return payload and the ambiguity rule. Every sentence 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 usefully names the returned artifacts (model IDs, printerBuildVolume objects) and covers the multi-match case. Minor gaps remain: the search granularity implied by 'limit' and the no-match behavior are unaddressed.

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 50%: 'query' is well documented with examples in the schema itself, while 'limit' is undocumented in both schema and description. The description implies name-based lookup but adds no syntax or interpretation guidance beyond the schema's own example.

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 ('Look up a named 3D printer in the Extrabold Tools catalog') and distinguishes itself implicitly from the generate_* siblings by framing its output as input for generation tools. It never names a specific sibling to route away from, so it stops short of full differentiation.

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 clear context for use: this resolves model IDs and build-volume objects 'ready for generation tools,' and it instructs the agent to ask the user to choose when multiple models match. It offers no explicit when-not or named alternative, so it is context without exclusions rather than a routing rule.

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/idempotentHint/destructiveHint=false, so the safety profile is covered. The description adds real behavioral value beyond that: it enumerates what is returned (full-unit grid, leftover margins, printer fit, warnings, URL) and explains the conditional splitting trigger tied to printerBuildVolume. It stops short of covering validation failures or the meaning of warnings.

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 sentences, no filler. The core scope constraint is front-loaded in the first sentence, output contents second, and the key cross-tool input hint third. Every sentence carries information an agent needs.

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 29-parameter, nested-object tool with no output schema, the description usefully summarizes the return payload and the splitting behavior, which is the highest-value missing context. It is not exhaustive about the many optional connector/magnet/split flags, but those are documented in the schema itself.

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 62%, above the baseline threshold, and the schema already documents the non-obvious parameters (tolerance, partsConnector, magnetHoleStyle, connectMarginCrossings). The description only adds meaning for dimensions and printerBuildVolume; for a 29-parameter tool the remaining gap in schema coverage is not compensated in prose. Baseline 3 is appropriate.

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 (Configure/Generate) plus resource (Gridfinity baseplate) and immediately scopes it: 'from exact width and depth in millimeters, without a drawer preset.' The phrase 'without a drawer preset' explicitly distinguishes it from the sibling generate_gridfinity_drawer_baseplate, so an agent can route correctly without opening 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 clear context: use this when you have raw width/depth measurements rather than a drawer preset, and it names the upstream dependency ('Supply printerBuildVolume from find_gridfinity_printers to enable automatic splitting'). It does not explicitly state when to prefer create_gridfinity_baseplate_url or the drawer variant, so it falls short of a full when/when-not/alternatives statement.

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, idempotentHint=true and destructiveHint=false, so the safety profile is covered. The description adds that splitting is auto-enabled when the plate doesn't fit, but that behavior is also conveyed by the splitToBuildplates schema text ('Override the automatic printer-fit split decision'), and nothing is said about what the tool returns or how split results are delivered.

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 front-loaded sentences with no filler: the core action comes first, followed by the input guidance and the auto-splitting behavior. Every sentence 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 27-parameter tool with nested objects, four enums, no output schema and only 30% schema description coverage, the description is far too thin. It omits the return value, how a split result is surfaced, and any orientation around the large option surface an agent must navigate to call this correctly.

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 30% across 27 parameters, so the description bears heavy compensation burden but supplies almost none. It only gestures at measured drawer dimensions and printer build volume — parameters whose schema entries already explain themselves — leaving the other ~19 options (tolerance, baseplateType, splitStrategy, connectors, magnets, etc.) undocumented in the 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 ('Generate a Gridfinity baseplate') scoped to a 'known drawer preset', which separates it from the generic sibling generate_gridfinity_baseplate. An agent can tell it produces a drawer-sized plate keyed off a preset, but the description never explicitly names the sibling it contrasts with.

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 conditional guidance ('Supply measured drawer dimensions when available'), which tells the agent when measuredDimensions is worth filling in. However, it never names alternatives (e.g. generate_gridfinity_baseplate or find_gridfinity_drawer_presets for obtaining the preset id) or states when NOT to use this tool, so usage is implied rather than specified.

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, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is covered. The description adds only that the call returns calculated millimeter dimensions and a shareable Extrabold Tools URL; it says nothing about defaults, whether splitting behavior is triggered, or how the URL is persisted, which would matter for a 29-parameter geometry tool.

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?

A single front-loaded sentence with no filler; the verb and resource come first and the output note follows. It is lean, though for a tool with 29 parameters it is arguably thinner than 'appropriately sized' implies.

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?

No output schema exists, so the description must carry return-value explanation; it gives only a one-line summary. For a 29-parameter tool with nested objects, printer build volumes, split strategies, and connector options, there is no guidance on the splitting model, defaults, or practical constraints, leaving significant gaps.

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 66%, so the schema documents most parameters itself. The description only echoes the required columns/rows concept and never touches the many geometry, tolerance, magnet, or split options; the baseline 3 applies since the description adds essentially nothing beyond the schema.

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 ('Generate a Gridfinity baseplate grid by columns and rows') and even characterizes the output (mm dimensions plus a shareable URL). However, it never distinguishes itself from the sibling generate_gridfinity_baseplate or generate_gridfinity_drawer_baseplate, so an agent cannot tell from the text which of the baseplate-producing tools to pick.

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, no exclusions, and no named alternatives despite six sibling tools with overlapping names. The agent is left to infer that 'grid by columns and rows' is the selecting condition, which is weak routing guidance.

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 cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's remaining burden is to explain the interaction model. The vague clause 'using Extrabold Tools setting descriptions and dependencies' does not say how questions are sequenced, whether the supplied parameters change the returned set, or how the caller knows it is done.

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?

A single front-loaded sentence with no filler; it is not verbose. The brevity is a weakness in substance rather than a structural flaw, which is captured in the other dimensions.

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 26 configuration parameters, no output schema, and only safety annotations, the description is far too thin. It does not explain the shape of the returned questions, the termination condition, or the role of the passed-in settings — the agent cannot confidently call this correctly.

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?

There are 26 parameters at only 12% schema description coverage, and the description adds nothing about any of them — not even that the already-supplied settings (rows, columns, baseplateType, tolerance, etc.) determine which questions are returned next. With this many undocumented inputs, the description fails to compensate for the schema 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?

The description names a specific verb and resource ('Return the next ... configuration questions to ask'), which is better than a tautology, but the actual purpose of the tool — driving a step-by-step configuration wizard — is only implied. It never distinguishes itself from the generate_* siblings or explains why an agent would fetch questions instead of generating a baseplate directly.

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 guidance on when to call this versus the five generate_* / find_* siblings, nor any prerequisite such as 'call repeatedly until no questions remain'. The agent must infer the interactive loop entirely on its own.

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