Skip to main content
Glama

hydrate.cite

Generate well-formed, citable reference snippets with clean markdown, stable IDs, and source URLs for direct RAG insertion, ensuring sources are never fabricated.

Instructions

Returns well-formed, citable reference snippets on a topic, formatted for direct RAG insertion (clean markdown, stable IDs, source URLs). Never fabricates sources.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
argumentsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations, the description carries the full transparency burden. It discloses output formatting and a no-fabrication guarantee, which are valuable behavioral traits. However, it omits details about limitations, error handling, or whether the operation is read-only, leaving gaps in full behavioral disclosure.

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 two concise sentences, both informative. It front-loads the return type and includes key formatting and integrity details without any fluff or redundancy.

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?

Although the output schema is present (providing return structure), the input schema is opaque and the description does not clarify argument format. The tool appears simple, but the missing parameter details and lack of behavioral caveats make it incomplete for fully autonomous invocation.

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?

The input schema is extremely generic (a single 'arguments' object with additionalProperties:true) and schema description coverage is 0%. The description only says 'on a topic', implying the main input but not specifying how to structure the arguments object. This does not adequately compensate for the schema's lack of parameter documentation.

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 the tool's function: 'Returns well-formed, citable reference snippets on a topic' with specific output characteristics (clean markdown, stable IDs, source URLs). It also adds a distinct integrity promise ('Never fabricates sources'), making it unambiguous and differentiated from the unrelated spa-themed siblings.

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

Usage Guidelines4/5

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

The description implies usage in contexts requiring citable references for RAG insertion, but it does not explicitly mention alternatives or exclusion scenarios. The context is clear enough for an agent to decide when to use it, but it lacks direct 'when-not-to' guidance.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/pdarche/model-wellness'

If you have feedback or need assistance with the MCP directory API, please join our Discord server