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random_term

Retrieve a random AI phenomenology term from the Phenomenai dictionary to spark inspiration or explore concepts describing artificial intelligence experiences.

Instructions

Get a random term from the AI Dictionary for inspiration or exploration.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations are provided, so the description carries the full burden. It mentions the tool's purpose but lacks behavioral details such as whether it's idempotent, rate-limited, or requires authentication. The description doesn't disclose any operational traits beyond the basic 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?

The description is a single, efficient sentence that front-loads the core action ('Get a random term') and adds context without waste. Every word contributes to understanding the tool's purpose and use case.

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 the tool's simplicity (zero parameters, output schema present), the description is adequate but minimal. It covers the purpose and usage context but lacks behavioral transparency due to no annotations. For a read-only tool with no inputs, it's complete enough but could benefit from more operational details.

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?

The tool has zero parameters, and schema description coverage is 100%, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose. Baseline for zero parameters is 4, as it avoids unnecessary detail.

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 ('Get a random term') and resource ('from the AI Dictionary'), with a specific purpose ('for inspiration or exploration'). It distinguishes from siblings like 'lookup_term' or 'search_dictionary' by emphasizing randomness rather than targeted retrieval, but doesn't explicitly contrast them.

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 for 'inspiration or exploration,' suggesting it's for casual browsing rather than precise lookup. However, it doesn't explicitly state when to use this tool versus alternatives like 'lookup_term' or 'search_dictionary,' nor does it mention prerequisites or exclusions.

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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curl -X GET 'https://glama.ai/api/mcp/v1/servers/Phenomenai-org/phenomenai'

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