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hydrate.cite

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

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries full burden. It discloses return format and non-fabrication, but fails to mention any limitations, authentication, rate limits, or scope of topics. The single behavioral claim is positive but incomplete.

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?

Two sentences with no waste. The main action and output format are front-loaded. Could be slightly more structured with bullet points, but overall efficient.

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

Completeness1/5

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

Given a vague single parameter and no annotations, the description is severely incomplete. An agent cannot determine how to invoke the tool correctly (what to put in 'arguments') or understand its full behavior.

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 coverage is 0% because 'arguments' is a generic object. The description only implies a topic parameter but does not specify required structure or keys. It fails to compensate for the 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 returns well-formed reference snippets with specific formatting (clean markdown, stable IDs, source URLs) and asserts non-fabrication. It clearly differentiates from sibling tools which are unrelated spa activities.

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 guidance on when to use this tool or alternatives. It mentions 'on a topic' but gives no prerequisites or exclusions. Sibling tools are unrelated, but still lacks explicit context for appropriate usage.

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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TDQS

B3.3/5.0
Disambiguation4/5

Most tools have clearly distinct purposes (e.g., critiques, affirmations, citation generation). However, spa.checkout and spa.keepsake both involve returning a keepsake instruction, which could cause confusion. Overall, ambiguity is minimal.

Naming Consistency5/5

All tools follow a consistent 'category.verb' or 'category.noun' pattern (e.g., affirmations.daily, spa.checkin, hydrate.cite). This makes it easy for an agent to infer tool purpose from the name.

Tool Count5/5

14 tools is a well-scoped set for the 'model wellness' domain. Each tool has a distinct function, and the count is neither excessive nor too sparse, fitting within the typical 3-15 range.

Completeness4/5

The tool surface covers core wellness activities: affirmations, feedback, session management, context cleanup, security, and reference generation. Minor gaps exist, such as the lack of a tool for model training or performance logging, but the core workflows are solid.