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siffletdata

sifflet-mcp

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by siffletdata

get_downstream_assets_of_asset

Identify all downstream assets impacted by a given asset using its unique URN. Assess data lineage and dependency impact for data observability.

Instructions

      Get all downstream assets of an asset. An Urn is the unique identifier of an asset, for example dataset:0826ce5c-7027-4857-aa47-b639265d1867. It can be found when you search for an asset.
      

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urnYes
Behavior2/5

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

With no annotations, the description must carry the burden of behavioral disclosure. It only states what the tool does, not details like whether it's read-only, what constitutes 'downstream' (immediate vs transitive), or if pagination or limits apply. The description adds an example of an urn but no behavioral traits beyond the core action.

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?

Two sentences with no fluff. The first states the core purpose, and the second adds necessary parameter context with an example. It's appropriately sized and front-loaded.

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

Completeness3/5

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

For a simple one-parameter tool, the description covers the action and parameter well, but it lacks information about the return value or semantics of 'downstream'. It might be sufficient for a simple use case, but given no output schema, a hint about what the response contains would improve completeness.

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 0%, so the description must compensate. It explains what an Urn is, provides an example format, and tells how to obtain it ('It can be found when you search for an asset'). This adds meaningful context beyond the schema's bare 'string' type.

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 first sentence clearly states the verb and resource: 'Get all downstream assets of an asset.' This distinguishes it from sibling tools like asset_by_urn (single asset) and search_asset (search), as it focuses on downstream assets.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool vs alternatives. It does explain how to obtain the urn (by searching for an asset), but that's a prerequisite, not a usage context. There's no mention of 'use this to see dependencies' or comparisons with sibling tools.

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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