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@lando-labs/lando-ds-mcp

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by lando-labs

get_composition_hints

Get composition hints for any Lando DS component, showing which component or shape each prop expects. Use to resolve prop types and compose components correctly.

Instructions

DS-authoritative composition hints for a component — for each documented prop, which component (or shape) it expects. Sourced from meta.verbose.composes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
componentNameYesPascalCase component name (e.g. "Button", "DatePicker").
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses that the data is sourced from 'meta.verbose.composes' and only covers 'documented props,' which is useful context. However, it does not describe return format, error behavior for invalid component names, or whether the data is always available for every component.

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?

The description is a single sentence with a clear, front-loaded purpose followed by a source note. Every word earns its place; no fluff or repetition of schema details.

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?

For a simple read tool with one parameter and no output schema, the description adequately explains the return concept ('for each documented prop, which component (or shape) it expects'). It could be slightly more explicit about the exact output structure, but overall it is complete enough for an agent to select and invoke the tool correctly.

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

Parameters3/5

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

The schema already provides complete coverage of the single parameter (componentName) with a clear description and enum. The tool description does not add additional meaning about the parameter beyond what the schema states, so the baseline of 3 is appropriate.

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 clearly states that it provides 'DS-authoritative composition hints for a component' and specifies exactly what it returns: 'for each documented prop, which component (or shape) it expects.' This distinguishes it from sibling tools like get_component_props (prop types) or compose_components (actual composition).

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

Usage Guidelines3/5

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

The description implies usage when composition hints are needed, but it does not explicitly state when to use this tool over alternatives or provide exclusion criteria. There is no mention of when not to use it or which sibling tool might be a better fit for other scenarios.

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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