random_quoteGet a random anime quote. Returns quote text, character name, and anime series title.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| anime | Yes | Title of the anime series | |
| quote | Yes | The anime quote text | |
| character | Yes | Name of the character who said the quote |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Input schema / examplesAdded value: +[
+ {}
+]Output schema / (root)Previous value: -nullNew value: +{
+ "properties": {
+ "anime": {
+ "description": "Title of the anime series",
+ "type": "string"
+ },
+ "character": {
+ "description": "Name of the character who said the quote",
+ "type": "string"
+ },
+ "quote": {
+ "description": "The anime quote text",
+ "type": "string"
+ }
+ },
+ "required": [
+ "quote",
+ "character",
+ "anime"
+ ],
+ "type": "object"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds the crucial behavioral trait of randomness, which is not covered by annotations, and also names the returned fields. This enriches the agent's understanding beyond the structured safety hints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short, front-loaded sentences. The first sentence states the action, and the second lists the output. Every word is purposeful, with no repetition or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (no parameters), the presence of a rich annotation set, and the existence of an output schema (which likely documents return structures), the description is complete. It covers purpose, output, and the key behavioral nuance of randomness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description doesn't need to explain parameters, but it doesn't add any harm. The schema is complete with an empty properties object, and the description's mention of return fields is relevant though not parameter-related.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Get a random anime quote' with a specific verb and resource, and it also lists the return fields (quote text, character name, anime series title). This distinguishes it from sibling search tools like search_by_anime and search_by_character.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives clear context for when to use the tool: when a random anime quote is needed. It does not explicitly mention alternatives or exclusions, but the purpose is self-evident and the lack of parameters makes it straightforward. There is no explicit when-not guidance, but it is not misleading.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Several tools occupy blurred boundaries: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, deep_research, and validate_claim all route questions to overlapping data pipelines, and the Polymarket family (bet_research, polymarket_edges, polymarket_arbitrage, polymarket_fill_risk, polymarket_kalshi_spread) heavily overlaps in purpose. Individual descriptions are detailed, but an agent must read long text to avoid misselection, especially when the three anime-quote tools are surrounded by unrelated tool families.
Most tools use snake_case and many begin with verbs (ask_, search_, resolve_, scan_, compare_, validate_), but several are noun-first or noun-phrase names like entity_profile, bet_research, random_quote, recent_alerts, recent_changes, and pipeworx_trending. There is no chaotic camelCase/snake_case mix, but the convention is not applied consistently enough for a predictable pattern.
34 tools is heavy for any single-purpose server, and the vast majority have nothing to do with anime quotes—they are Pipeworx data tools, prediction-market tools, subscription tools, memory tools, and AI-audit tools. For a server named animequotes, only random_quote, search_by_anime, and search_by_character fit the stated purpose, making the count wildly disproportionate.
For the apparent anime-quote domain, random_quote, search_by_anime, and search_by_character cover basic lookup but leave notable gaps: no search by quote text, no quote-by-id fetch, no ability to list all series or characters, and no pagination or metadata browsing. The unrelated tools do not fill these gaps, so the anime-quote surface is functional but incomplete.