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Quotes

by io.github.pipeworx-io

Random Quote

random_quote
Read-onlyIdempotent

Return a random quote from the corpus, optionally filtered by author, fame, verification status, or tag. Each result includes citation: work, year, speaker (for plays/fiction), and source URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoFilter by tag (e.g., "wit", "love", "misattributed", "commonly-misquoted").
author_idNoOptional author id (e.g., "oscar-wilde", "william-shakespeare", "mark-twain"). Use list_authors to discover ids.
famous_onlyNoIf true, only return famous/canonical quotes.
verified_onlyNoIf true, exclude misattributed quotes.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.1/5.0
Behavior4/5

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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds value by describing the result structure (citation with work, year, speaker, source URL), which goes beyond annotations.

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 zero waste. First sentence states primary action and filters; second describes output. Perfect front-loading of key information.

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

Completeness5/5

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

Given the simple tool with 4 optional parameters, comprehensive annotations, and an existing output schema, the description is fully complete. It covers purpose, filters, and result content without needing to detail return values.

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

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description mentions filter options that match the schema but adds no new meaning beyond what the parameter descriptions already provide.

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 it returns a random quote from a corpus with optional filters, and specifies result contents (citation info). This distinguishes it from siblings like search_quotes which return filtered results.

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 does not explicitly state when to use this tool versus alternatives. While the name and purpose imply it's for random quotes, no guidance on when not to use it or which sibling to prefer is provided.

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

A3.8/5.0
Disambiguation3/5

The tool set includes multiple similar tools (e.g., three ask_pipeworx variants, several Polymarket tools) that could cause agent confusion. While each has a distinct purpose, the boundaries are subtle and descriptions lean heavily on jargon, making misselection likely.

Naming Consistency4/5

All tool names use snake_case consistently. Most follow a noun_verb or verb_noun pattern, but some (e.g., ai_visibility_check, bet_research) start with a subject rather than an action, breaking a strict verb-first convention.

Tool Count2/5

With 40 tools, the server feels overloaded. The name 'Quotes' suggests a narrow focus, yet the tool set spans fact-checking, company research, prediction markets, and more. Many tools are highly specialized or meta-tools, inflating the count without clear necessity.

Completeness3/5

The server covers a wide range of use cases, from quotes and literature to financial data and prediction markets. However, there are noticeable gaps in core areas (e.g., basic CRUD for quotes beyond search and random), and the sheer breadth creates dead ends for deep workflows.

Resources