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attach_computation_data_assets

Attach data assets to cloud workstation computations by specifying IDs and optional mount paths for workflow integration.

Instructions

Attach one or more data assets to a cloud workstation session computation. Accepts a list of parameter objects (e.g. [{'id': '...'}]). Use for cloud workstation sessions.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
computation_idYes
attach_paramsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

With no annotations provided, the description carries full burden but offers limited behavioral insight. It mentions the tool accepts a list of parameter objects, hinting at input format, but doesn't disclose permissions, side effects, rate limits, or what happens on success/failure. For a mutation tool, this is inadequate.

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 brief and front-loaded with the core purpose, using two sentences efficiently. However, the example syntax could be more integrated, and it lacks structural elements like bullet points for clarity, but overall it avoids unnecessary verbosity.

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?

Given 2 parameters with 0% schema coverage, an output schema exists (which reduces need to describe returns), and no annotations, the description is moderately complete. It covers the basic action and input format but misses behavioral details and full parameter explanations, making it adequate but with clear gaps for a mutation tool.

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

Parameters2/5

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 but adds minimal value. It notes 'Accepts a list of parameter objects (e.g. [{'id': '...'}])', which clarifies 'attach_params' as an array with ID fields, but doesn't explain 'computation_id' or details like mount paths. This partially addresses one parameter but leaves gaps.

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

Purpose4/5

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

The description clearly states the action ('Attach') and target ('data assets to a cloud workstation session computation'), making the purpose understandable. It distinguishes from siblings like 'detach_computation_data_assets' by specifying attachment, though it doesn't explicitly contrast with 'attach_data_assets' which might be for different contexts.

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?

The description provides minimal guidance with 'Use for cloud workstation sessions,' but lacks explicit when-to-use criteria, prerequisites, or comparisons to alternatives like 'attach_data_assets.' No exclusions or detailed context are given, leaving usage ambiguous.

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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